The burdens and challenges of discovery—especially electronic discovery—are usually associated with civil, not criminal cases. This is beginning to change. Already common in white-collar crime cases, voluminous digital discovery is increasingly a feature of ordinary criminal prosecutions.\nThis Article examines the explosive growth of digital evidence in criminal cases and the efforts to manage its challenges. It then advances three claims about criminal case discovery in the digital age. First, the volume, complexity, and cost of digital discovery will incentivize the prosecution and the defense to cooperate more closely in cases with significant amounts of electronically stored information (ESI). Second, cooperation between the parties will not be sufficient to address the serious challenges that digital discovery presents to the fair and accurate resolution of criminal cases. And third, for that reason, digital discovery in criminal cases needs to be regulated more closely.\nIn crafting such regulation, courts and legislators can build on the civil procedure model, which has grappled with the challenges of electronic discovery for over two decades. The civil procedure experience suggests that cooperation between the parties, active judicial involvement, and more detailed rules are essential to the effective management of digital discovery.\nThe civil litigation model has its limitations, however, and policymakers must chart new ground to address some of the unique demands of criminal cases. Recognizing the significant resource and bargaining disparities in criminal cases, judges need to limit certain negotiated waivers of discovery so as to prevent abuse. Where the interests of justice demand it, courts may also need to help defendants obtain access to digital discovery in detention or gather digital evidence from third parties. These and other measures can help ensure that the cost and complexity of digital discovery do not undermine the fairness and accuracy of criminal proceedings.
Entanglement is a crucial resource for quantum technologies ranging from quantum communication to quantum-enhanced measurements and computation. Finding experimental setups for these tasks is a conceptual challenge for human scientists due to the counterintuitive behavior of multiparticle interference and the enormously large combinatorial search space. Recently, new possibilities have been opened by artificial discovery where artificial intelligence proposes experimental setups for the creation and manipulation of high-dimensional multi-particle entanglement. While digitally discovered experiments go beyond what has been conceived by human experts, a crucial goal is to understand the underlying concepts which enable these new useful experimental blueprints. Here, we present Halo (Hyperedge Assembly by Linear Optics), a new form of multiphoton quantum interference with surprising properties. Halos were used by our digital discovery framework to solve previously open questions. We -- the human part of this collaboration -- were then able to conceptualize the idea behind the computer discovery and describe them in terms of effective probabilistic multi-photon emitters. We then demonstrate its usefulness as a core of new experiments for highly entangled states, communication in quantum networks, and photonic quantum gates. Our manuscript has two conclusions. First, we introduce and explain the physics of a new practically useful multi-photon interference phenomenon that can readily be realized in advanced setups such as integrated photonic circuits. Second, our manuscript demonstrates how artificial intelligence can act as a source of inspiration for the scientific discoveries of new actionable concepts in physics.
Digital discovery of functional materials, such as metal-organic frameworks (MOFs), entails accurate and data-efficient approaches to navigate complex chemical and structural space. Based on an innovative deep learning approach, namely, Kolmogorov-Arnold Networks (KANs), we introduce MOF-KAN, a state-of-the-art architecture as the first application of KANs to digital discovery of MOFs. Through meticulous fine-tuning of network architecture, we demonstrate that MOF-KAN outperforms standard multilayer perceptrons (MLPs) in predicting diverse properties for MOFs, including gas separation, electronic band gap, and thermal expansion. Furthermore, MOF-KAN excels in low-data regimes, facilitating robust performance in challenging prediction scenarios. Feature importance analysis reveals that MOF-KAN accurately captures critical features of MOFs relevant to targeted properties. MOF-KAN not only serves as a transformative tool for the rational design of functional materials but also holds broad applicability across various domains in physical sciences.
Digital Discovery and Fake ImprintsUnmasking Turn-of-the-Century Pornographers in Paris Colette Colligan (bio) By the end of the nineteenth century there was a flourishing cross-border trade in pornographic books in Western Europe. The production center was Paris, where the law of 29 July 1881 guaranteed considerable freedom of the press and where the book, in particular, benefitted from special cultural protections under the country's obscenity law of 2 August 1882. Producers of pornographic books, however, could still be criminally prosecuted in the country's highest court on the grounds of immorality. As a consequence they carefully concealed their identities and publishing activities. One of the most visible of these publishers was Charles Carrington (1867–1921), an Englishman who in 1895 relocated to Paris, where he ran a bookshop and published roughly 300 different titles in English and French.1 He published some of his books under an open imprint bearing his name (in fact his pseudonym, for he was born Paul Ferdinando), while others he published clandestinely, outside legal deposit. We know much about Carrington's Anglo-French operations, even from his own pen, but there is little known about other producers active at the same time in overlapping roles as publishers, printers, and booksellers. Bibliographers specializing in clandestine pornography have done the most to reconstruct the lives, careers, and book lists of these other pornographers, but as Peter Mendes admits, "terms like 'probable', 'possible', 'likely', 'conjecture', and 'surmise'" [have] figure[d] extensively."2 Most of those responsible for putting pornographic writing in circulation in the period have thus remained obscure, limiting our understanding of the types of individuals and social networks that made up this subculture. The difficulty in unmasking clandestine publishers who were operating out of Paris between the 1880s and 1920s has been threefold. First of all, traditional publishers' archives do not exist. Secondly, the names of publishers that have been passed down in bibliographic sources are often incomplete. [End Page 249] Digging through French physical archives for a surname (which also might be a pseudonym or some corruption of the original) necessitates much labor, time, and patience, as indexing is minimal and access is limited. Finally, even if such sources were abundant, physical archives are typically bound by geographical borders, so that the paper trail ends when publishers moved (which they did for job opportunities and to flee the authorities). As one bibliographer once colorfully described the situation, "Often important discoveries are made quite by accident in dusty corners of old bookshops or hidden away in their cellars."3 This century's digital turn, however, has turned many of these old book-shops, dank cellars, and intractable archives into online platforms and databases, which (as observed by Sarah Bull) have transformed research on the history of pornography.4 The mass digitization of public records and historical newspapers as well as their aggregation into databases equipped with search algorithms and faceted navigation has immensely facilitated the process of tracking down the period's clandestine pornographers across multiple regional and national borders. Digital discovery can now lay bare the secret lives of a number of these individuals for the first time. That said, there is currently no "one-stop shop" database for cross-searching and cross-browsing European government records or newspapers. Rather, there is a diverse set of digital resources that need to be cross-referenced. The most useful digital resources have been the Ancestry website (an international commercial database of public records), French open-access regional and municipal archives (often simply digital scans), Gallica (the French national library's full-text digital library), and BelgicaPress (the Belgian national library's collection of digitized newspapers). A typical search begins with a boolean query in Gallica or BelgicaPress (entering a last name plus a keyword like "obscenité" or "pornographie") to unearth names, dates, and addresses (usually furnished from police and crime reports). This information then guides further research of vital records collected in Ancestry and regional archives. The discovery process then frequently leads back to site-based searching in physical archives, in particular non-digitized Parisian and Belgian judicial and prison records, which provide fascinating details about outlaw careers in print. Digital discoveries...
Photons are the physical system of choice for performing experimental tests of the foundations of quantum mechanics. Furthermore, photonic quantum technology is a main player in the second quantum revolution, promising the development of better sensors, secure communications, and quantum-enhanced computation. These endeavors require generating specific quantum states or efficiently performing quantum tasks. The design of the corresponding optical experiments was historically powered by human creativity but is recently being automated with advanced computer algorithms and artificial intelligence. While several computer-designed experiments have been experimentally realized, this approach has not yet been widely adopted by the broader photonic quantum optics community. The main roadblocks consist of most systems being closed-source, inefficient, or targeted to very specific use-cases that are difficult to generalize. Here, we overcome these problems with a highly-efficient, open-source digital discovery framework PyTheus, which can employ a wide range of experimental devices from modern quantum labs to solve various tasks. This includes the discovery of highly entangled quantum states, quantum measurement schemes, quantum communication protocols, multi-particle quantum gates, as well as the optimization of continuous and discrete properties of quantum experiments or quantum states. PyTheus produces interpretable designs for complex experimental problems which human researchers can often readily conceptualize. PyTheus is an example of a powerful framework that can lead to scientific discoveries – one of the core goals of artificial intelligence in science. We hope it will help accelerate the development of quantum optics and provide new ideas in quantum hardware and technology.
The Cancer Gene Anatomy Project database of the National Cancer Institute has thousands of expressed sequences, both known and novel, in the form of expressed sequence tags (ESTs). These ESTs, derived from diverse normal and tumor cDNA libraries, offer an attractive starting point for cancer gene discovery. Using a data-mining tool called Digital Differential Display (DDD) from the Cancer Gene Anatomy Project database, ESTs from six different solid tumor types (breast, colon, lung, ovary, pancreas, and prostate) were analyzed for differential expression. An electronic expression profile and chromosomal map position of these hits were generated from the Unigene database. The hits were categorized into major classes of genes including ribosomal proteins, enzymes, cell surface molecules, secretory proteins, adhesion molecules, and immunoglobulins and were found to be differentially expressed in these tumorderived libraries. Genes known to be up-regulated in prostate, breast, and pancreatic carcinomas were discovered by DDD, demonstrating the utility of this technique. Two hundred known genes and 500 novel sequences were discovered to be differentially expressed in these select tumor-derived libraries. Test genes were validated for expression specificity by reverse transcription-PCR, providing a proof of concept for gene discovery by DDD. A comprehensive database of hits can be accessed at http:// www.fau.edu/cmbb/publications/cancergenes. htm. This solid tumor DDD database should facilitate target identification for cancer diagnostics and therapeutics.
INTRODUCTION: The concept of Digital Twins (DTs) translated to drug development and clinical trials describes virtual representations of systems of various complexities, ranging from individual cells to entire humans, and enables in silico simulations and experiments. DTs increase the efficiency of drug discovery and development by digitalizing processes associated with high economic, ethical, or social burden. The impact is multifaceted: DT models sharpen disease understanding, support biomarker discovery and accelerate drug development, thus advancing precision medicine. One way to realize DTs is by generative artificial intelligence (AI), a cutting-edge technology that enables the creation of novel, realistic and complex data with desired properties. AREAS COVERED: The authors provide a brief introduction to generative AI and describe how it facilitates the modeling of DTs. In addition, they compare existing implementations of generative AI for DTs in drug discovery and clinical trials. Finally, they discuss technical and regulatory challenges that should be addressed before DTs can transform drug discovery and clinical trials. EXPERT OPINION: The current state of DTs in drug discovery and clinical trials does not exploit the entire power of generative AI yet and is limited to simulation of a small number of characteristics. Nonetheless, generative AI has the potential to transform the field by leveraging recent developments in deep learning and customizing models for the needs of scientists, physicians and patients.
There has been a great deal of interest in the concept, development and implementation of medical digital twins. This interest has led to wide ranging perceptions of what constitutes a medical digital twin. This Perspectives article will provide 1) a description of fundamental features of industrial digital twins, the source of the digital twin concept, 2) aspects of biology that challenge the implementation of medical digital twins, 3) a schematic program of how a specific medical digital twin project could be defined, and 4) an example description within that schematic program for a specific type of medical digital twin intended for drug discovery, testing and repurposing, the Drug Development Digital Twin (DDDT).
Abstract In digital soil mapping, machine learning (ML) techniques are being used to infer a relationship between a soil property and the covariates. The information derived from this process is often translated into pedological knowledge. This mechanism is referred to as knowledge discovery. This study shows that knowledge discovery based on ML must be treated with caution. We show how pseudo‐covariates can be used to accurately predict soil organic carbon in a hypothetical case study. We demonstrate that ML methods can find relevant patterns even when the covariates are meaningless and not related to soil‐forming factors and processes. We argue that pattern recognition for prediction should not be equated with knowledge discovery. Knowledge discovery requires more than the recognition of patterns and successful prediction. It requires the pre‐selection and preprocessing of pedologically relevant environmental covariates and the posterior interpretation and evaluation of the recognized patterns. We argue that important ML covariates could serve the purpose of providing elements to postulate hypotheses about soil processes that, once validated through experiments, could result in new pedological knowledge. Highlights We discuss the rationale of knowledge discovery based on the most important machine learning covariates We use pseudo‐covariates to predict topsoil organic carbon with random forest Soil organic carbon was accurately predicted in a hypothetical case study Pattern recognition by random forest should not be equated to knowledge discovery
INTRODUCTION: that act as indicators of health outcomes and can be used to diagnose and monitor a number of chronic diseases and conditions. There are many challenges faced by digital biomarker development, including a lack of regulatory oversight, limited funding opportunities, general mistrust of sharing personal data, and a shortage of open-source data and code. Further, the process of transforming data into digital biomarkers is computationally expensive, and standards and validation methods in digital biomarker research are lacking. METHODS: . RESULTS: Here, we detail the general DBDP framework as well as three robust modules within the DBDP that have been developed for specific digital biomarker discovery use cases. CONCLUSIONS: The clear need for such a platform will accelerate the DBDP's adoption as the industry standard for digital biomarker development and will support its role as the epicenter of digital biomarker collaboration and exploration.
animal models, these digital technologies allow for continuous, longitudinal, and non-invasive monitoring in the home environment. This manuscript provides an overview of digital monitoring technologies for use in preclinical studies including their history and evolution, current engagement through use cases, and impact of digital biomarkers (DBs) on drug discovery and the 3Rs. We also discuss barriers to implementation and strategies to overcome them. Finally, we address data consistency and technology standards from the perspective of technology providers, end-users, and subject matter experts. Overall, this review establishes an improved understanding of the value and implementation of digital biomarker (DB) technologies in preclinical research.
Penggunaan bahan ajar dalam pembelajaran IPA sangat penting karena dapat meningkatkan efektivitas dalam peningkatan hasil belajar siswa Penelitian ini bertujuan untuk mengetahui adanya pengaruh penggunaan bahan ajar digital interaktif dalam pembelajaran IPA dengan model discovery learning terhadap prestasi belajar siswa kelas VIII MTsN 3 Ponorogo. Penelitian quasi-eksperimen ini menggunakan posttest-only group design. Pengambilan sampel menggunakan teknik purposive sampling. Hasil penelitian ini menunjukkan bahwa ada pengaruh yang signifikan dari penerapan bahan ajar digital interaktif dengan model discovery learning terhadap prestasi belajar siswa. Dengan demikian, penggunaan bahan ajar digital interaktif dengan model discovery learning bisa digunakan oleh guru untuk mengakomodasi kemampuan kognitif siswa sehingga prestasi belajar siswa dapat meningkat.
Despite the abundance of available urban data and the potential for reaching enhanced capabilities in the decision-making and management of city infrastructure, current data-driven approaches to knowledge discovery from city data often lack the capacity for collective data exploitation. Loosely defined data interpretation components, or disciplinary isolated interpretations of specific datasets make it easy to overlook necessary domain expertise, often resulting in speculative decision-making. Smart City Digital Twins are designed to overcome this barrier by integrating a more holistic analytics and visualization approach into the real-time knowledge discovery process from heterogeneous city data. Here, we present a spatiotemporal knowledge discovery framework for the collective exploitation of city data in smart city digital twins that incorporates both social and sensor data, and enables insights from human cognition. This is an initial step towards leveraging heterogeneous city data for digital twin-based decision-making.
Scientists revisiting mysterious 540-million-year-old microfossils from Brazil have overturned a major idea about early animal life。 What were once thought to be trails left behind by tiny worm-like creatures are now believed to be fossilized communities of bacteria and algae — some with remarkably preserved cells and organic material still intact
Scientists may have uncovered a surprising secret behind why life exists at all。 A new study suggests that the Universe’s fundamental constants — the deep physical rules that govern everything from atoms to stars — appear to sit within an incredibly narrow “sweet spot” that allows liquids to flow properly inside living cells。 Even tiny shifts in th
Scientists have uncovered a surprising secret hidden inside fat cells that could reshape how we think about obesity and metabolic disease。 A protein called HSL, long believed to simply release stored fat when the body needs energy, turns out to have a second job deep inside the nucleus of fat cells—helping keep those cells healthy and balanced。 Eve
We present the results from a survey of i-dropout objects selected from ~1550 deg^2 of multicolor imaging data from the Sloan Digital Sky Survey, to search for luminous quasars at z>5.8. Objects with i*-z*>2.2 and z*<20.2 are selected, and follow-up J band photometry is used to separate L and T type cool dwarfs from high-redshift quasars. We describe the discovery of three new quasars, at z=5.82, 5.99 and 6.28, respectively. Their spectra show strong and broad Ly alpha+NV emission lines, and very strong Ly alpha absorption, with a mean continuum decrement D_A > 0.90. The ARC 3.5m spectrum of the z=6.28 quasar shows that over a range of 300 A immediately blueward of the Ly alpha emission, the average transmitted flux is only 0.003 +/-0.020 times that of the continuum level, consistent with zero flux, and suggesting a tentative detection of the complete Gunn-Peterson trough. The existence of strong metal lines suggests early chemical enrichment in the quasar enviornment. The three new objects, together with the previously published z=5.8 quasar form a complete color-selected flux-limited sample at z>5.8. We estimate that at $z=6$, the comoving density of luminous quasars at M_1450 < -26.89 (h=0.5, Omega=1)is 1.1x10^-9 Mpc^-3. This is a factor of ~2 lower than that at z~5, and is consistent with an extrapolation of the observed quasar evolution at low-z. We discuss the contribution of quasars to the ionizing background at z~6. The luminous quasars discussed in the paper have central black hole masses of several times 10^9 M_sun by the Eddington argument. Their observed space density provides a sensitive test of models of quasar and galaxy formation at high redshift. (Abridged)
The authors present the discovery of seven quasars at z > 5.7, selected from {approx} 2000 deg{sup 2} of multicolor imaging data of the Sloan Digital Sky Survey (SDSS). The new quasars have redshifts z from 5.79 to 6.13. Five are selected as part of a complete flux-limited sample in the SDSS Northern Galactic Cap; two have larger photometric errors and are not part of the complete sample. One of the new quasars, SDSS J1335+3533 (z = 5.93), exhibits no emission lines; the 3-{sigma} limit on the rest-frame equivalent width of Ly{alpha}+NV line is 5 {angstrom}. It is the highest redshift lineless quasar known, and could be a gravitational lensed galaxy, a BL Lac object or a new type of quasar. Two new z > 6 quasars, SDSS 1250+3130 (z = 6.13) and SDSS J1137+3549 (z = 6.01), show deep Gunn-Peterson troughs in Ly{alpha}. These troughs are narrower than those observed among quasars at z > 6.2 and do not have complete Ly{beta} absorption.
We present observations of SDSSp J104433.04--012502.2, a luminous quasar at z=5.80 discovered from Sloan Digital Sky Survey (SDSS) multicolor imaging data. This object was selected as an i'-band dropout object, with i*=21.8 +/- 0.2, z*=19.2 +/- 0.1. It has an absolute magnitude M1450 = -27.2 (H_0 =50 km/s/Mpc, q0 = 0.5). The spectrum shows a strong and broad Ly alpha emission line, strong Ly alpha forest absorption lines with a mean continuum decrement D_A = 0.91, and a Lyman Limit System at z=5.72. The spectrum also shows strong OI and SiIV emission lines similar to those of quasars at z<= 5, suggesting that these metals were produced at redshift beyond six. The lack of a Gunn-Peterson trough in the spectrum indicates that the universe is already highly ionized at z ~ 5.8. Using a high-resolution spectrum in the Ly alpha forest region, we place a conservative upper limit of the optical depth due to the Gunn-Peterson effect of tau < 0.5 in regions of minimum absorption. The Ly alpha forest absorption in this object is much stronger than that in quasars at z<= 5. The object is unresolved in a deep image with excellent seeing, implying that it is unlensed. The black hole mass of this quasar is ~3 x 10^9 M_solar if we assume that it is radiating at the Eddington luminosity and no lensing amplification, implying that it resides in a very massive dark matter halo. The discovery of one quasar at M_1450 < -27 in a survey area of 600 deg^2 is consistent with an extrapolation of the observed luminosity function at lower redshift. The abundance and evolution of such quasars can provide sensitive tests of models of quasar and galaxy formation.