„Wie ist Geschichte a priori möglich?“ Algorithmische Vorhersage und die Aufgabe der Kritik

In late antiquity astrology held a key position among the accepted and well-reputed sciences. As ars mathematica closely connected with astronomy, it made its way into the highest political and philosophical orders of the Roman Empire and became the standard model of interpreting past, present, and future events. Although this is widely acknowledged by modern historians, most scholars assume that the application of astrological theories is limited to the 'pagan mind,' whereas Jewish and Christian theology is characterized by a harsh refutation of astrology's implications. As can easily be shown, this assumption is not the result of careful examination of the documentary evidence but of a preconceived and misleading opinion about the basic ideas of astrology, which led to an astonishing disregard of Jewish and Christian evidence for astrological concerns. This evidence has been either played down - if not neglected entirely - or labeled 'heretic,' thus prolonging the polemics of the 'church fathers' right into modernity. After having reviewed the biases of previous research into monotheistic astrology and its crucial methodological problems, I shall propose a different approach. Astrology has to be seen as a certain way of interpreting reality. In this regard it is the very backbone of esoteric tradition. I shall sketch the different discourses reflected in some late antiquity's Jewish and Christian documents. It will be shown that the astrological worldview of planetary and zodiacal correspondences was common to most of the sources. Examples will be presented for illustrating different adoptions of this attitude, namely the discourse of cult theology, the magical and mystical application of astrological knowledge, the debates concerning volition and determinism, and, finally, the use of astrology for political and religious legitimization.

The damage caused by the short-circuit current has become continuously more serious with the increase of the capacity of short-circuit in the power system. The prediction technology of short-circuit current is widely concerned in order to ensure the safe and reliable operation of the power grid. The basic of the planning and construction of the power system is to accurately predict the short-circuit current. It is not only a key technology for high-voltage circuit breaker to complete the phase-control process of short-circuits current but also fundamental for low-voltage power distribution systems to achieve full selective protection. The causes and hazards of short-circuit are briefly described and the main factors affecting short-circuit current are analyzed. Node prediction method, zero point prediction method and peak prediction method are listed as short-circuit current prediction methods. The research statuses of each type of short-circuit current prediction methods at home and abroad are summarized respectively. The superiorities and weaknesses of different prediction methods are analyzed and compared at length. The key research direction of short-circuit current prediction technology is proposed based on the current status and development trend of short-circuit current prediction.

A technique to cluster large area oceanic predictions of sound speed into quasi-range independent areas is presented. Oceanic models produce high fidelity predictions of the oceanic sound speed fields that enable large-scale simulation of acoustic propagation with reasonable accuracy. Unfortunately, the oceanic models can produce sound speed fields quicker than can be digested by current technologies in underwater acoustic performance prediction systems. The speed bottleneck can be broken in two ways, a long term improvement in prediction technologies, and a interim process that allows similar acoustic areas to be aggregated into range dependent regions while maintaining a high degree of fidelity with the performance prediction resulting from using the complete oceanic model output. The interim process created must be capable of reflecting changes in sound speed field that control water born energy, and the changes in the field that effect the interaction with the oceanic bottom. This study uses vertically integrated gradient of the sound speed field as a basis for creating quasi-range dependent areas. The integrated gradient, when applied over a restricted latitudinal extent, gives an estimate of the mean ray curvature in the wave-guide. Since the field is integrated over depth, the effects of water depth are included in the calculation. The nature of the interaction with the oceanic bottom is not included in this calculation. The variations in bottom loss over the region of interest will be integrated into the analysis at a latter stage. The quantity cannot be used to predict transmission loss, but indicates where similar propagation conditions occur. The method is shown to be sensitive to the characteristics of the deep sound channel, and changes in the near surface structure of the sound speed field. The method is sensitive to the vertical integration weighting, which needs to be investigated further. The method is applied to an oceanic region where variations in bottom effects are simple and relatively well understood. Incoherent acoustic transmission loss predictions are made from a single receiver depth to a single target depth for each of the longitude-latitude mesh points in the computational domain of the oceanic prediction model where the initial water depth is greater than both the receiver depth and the target depth to a maximum range of 100km. The transmission loss predictions are fitted to a two-parameter family of curves. The two-parameter family of curves accomplish two closely related goals: (1) the number of parameters that must be compared is minimized, and (2) the slight differences in range of maximum and minimum that so often cloud prediction comparisons are eliminated. The relationships between transmission loss parameters, and integrated gradient of the sound speed field are relatively well constrained. The relationships cluster into groups that are characterized by bottom type. The relationships between the two-parameter family of curves and the vertically integrated index are thus far diagnostic, the variations in parameter coefficient are large enough such that a prognostic relationship does not appear to be supported.

The COVID-19 pandemic and its aftermath are the most significant socio-economic crises in modern history. The pandemic’s devastating impacts have prompted urgent policy and regulatory action to reduce the risks of future spillover events and pandemics. Stronger regulatory measures for the trade of wildlife are central to discussions of a policy response. A variety of measures, including broad bans on the trade and sale of wildlife to banning specific species for human consumption are among a suite of discussed options. However, the wildlife trade is diverse, complex, and important for the livelihoods of millions of people globally. We argue that reducing the risk of future pandemics stemming from the wildlife trade must follow established principles of governance which include being equitable, responsive, robust, and effective. We demonstrate how incorporating these principles will support the development of context-specific, culturally sensitive, and inclusive responses that recognize the on-the-ground complexity of disease emergence and the social-ecological systems in which the wildlife trade occurs.

Decrease of mobility, electricity demand, and NO2 emissions on COVID-19 times and their feedback on prevention measures

The angiotensin-converting enzyme 2 (ACE2) receptor is a major severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) host range determinant, and understanding SARS-CoV-2-ACE2 interactions will provide important insights into COVID-19 pathogenesis and animal model development. SARS-CoV-2 cannot infect mice due to incompatibility between its receptor binding domain and the murine ACE2 receptor. Through molecular modeling and empirical in vitro validation, we identified 5 key amino acid differences between murine and human ACE2 that mediate SARS-CoV-2 infection, generating a chimeric humanized murine ACE2. Additionally, we examined the ability of the humanized murine ACE2 receptor to permit infection by an additional preemergent group 2B coronavirus, WIV-1, providing evidence for the potential pan-virus capabilities of this chimeric receptor. Finally, we predicted the ability of these determinants to inform host range identification of preemergent coronaviruses by evaluating hot spot contacts between SARS-CoV-2 and additional potential host receptors. Our results identify residue determinants that mediate coronavirus receptor usage and host range for application in SARS-CoV-2 and emerging coronavirus animal model development.IMPORTANCE SARS-CoV-2 (the causative agent of COVID-19) is a major public health threat and one of two related coronaviruses that have caused epidemics in modern history. A method of screening potential infectible hosts for preemergent and future emergent coronaviruses would aid in mounting rapid response and intervention strategies during future emergence events. Here, we evaluated determinants of SARS-CoV-2 receptor interactions, identifying key changes that enable or prevent infection. The analysis detailed in this study will aid in the development of model systems to screen emergent coronaviruses as well as treatments to counteract infections.

The Advancing Structural Simulation to drive Innovative Sustainment Technologies (ASSIST) collaborative program was initiated by Defence Science and Technology (DST) Group to foster improvements in fatigue life prediction technologies, with the long-term goal of a virtual fatigue test. It is based upon a growing series of airframe challenges, where participants are invited to test state-of-the-art fatigue prediction technologies on problems based on real aircraft structures and loads. Since each challenge is underpinned by a set of demonstrated test results, the predictive ability of all technologies can be accurately assessed. Furthermore, the collaborative forensic review of the challenge results is considered a key output, which will allow the limitations of predictive techniques to be better understood and addressed in future research.DST has established a collaborative online space for the ASSIST community at https://www.govteams.gov.au/. It is being used to share essential data associated with each challenge, provide a collaborative space for discussions, and post results and evaluations. The first ASSIST challenge has been completed and two further challenges have been released to the ASSIST community. The first ASSIST challenge, which was based on a fighter wing-root shear tie post, is described here. It demonstrated the critical importance of having accurate fatigue crack growth data, in addition to understanding the fatigue crack shape and local stress field when the crack depth is still very small. It is considered that future ASSIST challenges will provide many further insights, which will drive improvements to current fatigue life prediction technologies. It is envisaged that the growing database of ASSIST airframe challenges will provide an understanding of the accuracy that can be achieved with current fatigue life prediction methodologies. This is another important product of the program, because it enables the adoption of such methodologies on real aircraft structures.

In the field of power communication, the current fault prediction technology has the problem of imperfect prediction model, which leads to short prediction distance. This paper designs a field fault prediction technology of power communication based on Fuzzy Petri net. The fault influence degree is measured, the tolerance mechanism is established, the layer by layer propagation mode is obtained, the fault feature types are divided, the prediction model is constructed based on Fuzzy Petri net, and the resource of database is formed. Combined with the fuzzy set theory, the fault prediction process is designed by using subsection exchange ant colony algorithm. The experimental results show that the average distance between the other two prediction technologies and the designed fault prediction technology is 83.662km, 83.339km and 95.864km, respectively, which proves that the fault prediction technology combined with fuzzy Petri net is more suitable for power communication tasks.

Erosion by water on agricultural areas has been studied by USDA (SCS, ARS, FS, NRCS) since the 1930‘s, initially consisting of natural runoff plots at numerous locations in the country that provided data that culminated in the development of the Universal Soil Loss Equation (USLE) in 1965 in Agriculture Handbook 282 (Wischmeier and Smith, 1965). Rainfall simulation equipment developed by ARS scientists located at Purdue University during the early 1960‘s was used to supplement the natural rainfall plot data and provided the ability to rapidly study soil erosion processes in more controlled laboratory and field experiments. The USLE update in Agriculture Handbook 537 (Wischmeier and Smith, 1978) contained a soil erodibility nomograph, developed from the results of extensive field rainfall simulation studies across the Midwest U.S. Transitions to process-based soil erosion modeling approaches in the 1980‘s-1990‘s relied upon laboratory and field rainfall simulation experiments to study processes and develop parameterization approaches for sensitive model input parameters. The Water Erosion Prediction Project (WEPP) model solves differential equations down a slope profile, that compute changes in sediment load and detachment/deposition at discrete points (Flanagan and Nearing, 1995; Flanagan et al., 2001). Unfortunately, most data available for validation of process-based hillslope interrill/rill erosion is from natural runoff plots (USLE database) or other natural or simulated rainfall studies where soil (sediment) loss was only measured at the plot end. Newer experimental measurement techniques, equipment, and approaches are needed to allow examination of changes in sediment detachment/deposition/loads with very fine spatial resolution down a hillslope and down a rill channel. The current modeling techniques also assume either uniformly spaced rill channels down a slope profile (default is 1-m spacing), or alternately simulations can be conducted where all surface flow is assumed to be distributed at a uniform shallow depth across the entire flow width. However, in real world situations the soil conditions, landscape complexities and increases in slope lengths can result in situations where no evident rilling occurs, rill spacings change with increasing slope lengths, or surface flows converge or diverge which may result in channelized rill flows changing to broader sheet flows. These complex surface flow situations need to be accounted for in any new water erosion prediction technologies, as they can greatly affect soil detachment and deposition processes. Additionally, subsurface hydrology effects also need to be better accounted for in any new technologies. Current erosion prediction models poorly account for water moving within the soil, and how saturation conditions can weaken the soil surface and make it more susceptible to detachment. A comprehensive understanding of how subsurface water moves and can converge in fields (and may emerge to the surface) is needed in new modeling approaches that can also be linked to initiation and development of ephemeral gullies. Additionally, better understanding and modeling of the effects of subsurface drainage and controlled drainage systems on hydrology and soil erosion is required. This also highlights the needs to move to erosion prediction systems that truly represent the landscape and fields as 2-D/3-D surfaces. Current prediction technologies are largely limited to estimating soil erosion processes at points down a line to represent a rectangular area. Long-term temporal effects of various practices on soil health and soil hydrology and erosion also should be accounted for in new erosion models. Currently, baseline soil erodibility is assumed to be a constant value for a particular soil and cropping system as a function of soil texture, organic matter, and other properties. However, fields that are in long-term pasture, or long-term no-till row crop management systems along with the use of cover crops may substantially change soil organic matter, soil structure, infiltration characteristics, and erodibilities that are not currently reflected in USDA models. This presentation will explore these and other areas of research needed.

Erosion by water on agricultural areas has been studied by USDA (SCS, ARS, FS, NRCS) since the 1930‘s, initially consisting of natural runoff plots at numerous locations in the country that provided data that culminated in the development of the Universal Soil Loss Equation (USLE) in 1965 in Agriculture Handbook 282 (Wischmeier and Smith, 1965). Rainfall simulation equipment developed by ARS scientists located at Purdue University during the early 1960‘s was used to supplement the natural rainfall plot data and provided the ability to rapidly study soil erosion processes in more controlled laboratory and field experiments. The USLE update in Agriculture Handbook 537 (Wischmeier and Smith, 1978) contained a soil erodibility nomograph, developed from the results of extensive field rainfall simulation studies across the Midwest U.S. Transitions to process-based soil erosion modeling approaches in the 1980‘s-1990‘s relied upon laboratory and field rainfall simulation experiments to study processes and develop parameterization approaches for sensitive model input parameters. The Water Erosion Prediction Project (WEPP) model solves differential equations down a slope profile, that compute changes in sediment load and detachment/deposition at discrete points (Flanagan and Nearing, 1995; Flanagan et al., 2001). Unfortunately, most data available for validation of process-based hillslope interrill/rill erosion is from natural runoff plots (USLE database) or other natural or simulated rainfall studies where soil (sediment) loss was only measured at the plot end. Newer experimental measurement techniques, equipment, and approaches are needed to allow examination of changes in sediment detachment/deposition/loads with very fine spatial resolution down a hillslope and down a rill channel. The current modeling techniques also assume either uniformly spaced rill channels down a slope profile (default is 1-m spacing), or alternately simulations can be conducted where all surface flow is assumed to be distributed at a uniform shallow depth across the entire flow width. However, in real world situations the soil conditions, landscape complexities and increases in slope lengths can result in situations where no evident rilling occurs, rill spacings change with increasing slope lengths, or surface flows converge or diverge which may result in channelized rill flows changing to broader sheet flows. These complex surface flow situations need to be accounted for in any new water erosion prediction technologies, as they can greatly affect soil detachment and deposition processes. Additionally, subsurface hydrology effects also need to be better accounted for in any new technologies. Current erosion prediction models poorly account for water moving within the soil, and how saturation conditions can weaken the soil surface and make it more susceptible to detachment. A comprehensive understanding of how subsurface water moves and can converge in fields (and may emerge to the surface) is needed in new modeling approaches that can also be linked to initiation and development of ephemeral gullies. Additionally, better understanding and modeling of the effects of subsurface drainage and controlled drainage systems on hydrology and soil erosion is required. This also highlights the needs to move to erosion prediction systems that truly represent the landscape and fields as 2-D/3-D surfaces. Current prediction technologies are largely limited to estimating soil erosion processes at points down a line to represent a rectangular area. Long-term temporal effects of various practices on soil health and soil hydrology and erosion also should be accounted for in new erosion models. Currently, baseline soil erodibility is assumed to be a constant value for a particular soil and cropping system as a function of soil texture, organic matter, and other properties. However, fields that are in long-term pasture, or long-term no-till row crop management systems along with the use of cover crops may substantially change soil organic matter, soil structure, infiltration characteristics, and erodibilities that are not currently reflected in USDA models. This presentation will explore these and other areas of research needed.

Three-dimensional spatiotemporal wind field reconstruction based on physics-informed deep learning

The close relationship between protein sequence and structure plays an important role in current analysis and prediction technologies. PROSITE, PRINTS, and BLOCKS are three of the most popular motif databases. Granular computing represents information in the form of aggregates, also called information granules. For a huge and complicated problem, it applies the divide-and-conquer concept to split the original task into several smaller subtasks to save time and space complexity. The major advantages of the Fuzzy Greedy K-Means (FGK) model are reduced spatiotemporal complexity, filtered outliers, and higher-quality granular information results. Since the major purpose of this work is to obtain protein sequence motif information across protein family boundaries, the dataset of this work is intended to represent all known protein sequences. The dataset used in this work includes 2710 PDB protein sequences obtained from the Protein Sequence Culling Server (PISCES).

This article provides a genealogy of ‘smart’ border policing before computational and digital technologies, such as Blockchain or Artificial Intelligence gained traction in public administration. First, I analyse the European Union’s plans and desires for an interoperability framework in the areas of migration, border policing and security. I show that database interoperability is one of the largest concerns of European public administration in general, and border and migration policing in particular. Second, I focus on plans and implementations of database interoperability between public administration, border control, and policing, as they were articulated in the 1970s and 80s in Germany. Looking at archival documents about the reform of the Central Register of Foreigners, I analyse how public administration imagined and designed data interoperability between migration and policing institutions. I situate these plans as part of larger political concerns about anti-terrorism, labour migration, and European integration. I present three interrelated arguments. First, historically, I show how interoperability, as a technocratic administrative project, was and is continuously reproduced through the fabrication of political urgency and the governmental desire for seamless and unhindered information flow, a process I call infrastructural opportunism. Second, media-theoretically, I characterize interoperability as a theory of communication that is entangled with histories of modernity and empire. I argue that it is not only interoperability in itself that has efficacy in debates on reforming public administration, but that talking about interoperability produces its efficacy. Third, politically, I argue that we must strengthen abolitionist approaches in the study of databases and migration policing, as they provide fundamental structural critiques of border violence beyond reformist approaches to privacy and data protection. As such, this article contributes to the literature on digital migration and border policing, as well as the history of media technology.

Solving Dementia Mysteries

Around 300 000 people were killed by the tsunami that followed the Sumatra–Andaman earthquake on Boxing Day 2004, making it one of the worst disasters in modern history. Up to 40 000 died in Sri Lanka alone, where around 80 000 houses were also destroyed when waves up to 15 m high swept ashore. This paper reports on how coastal buildings and infrastructure in Sri Lanka behaved under various tsunami wave heights and the many lessons learned for reducing vulnerability to future events. In particular, newly published national guidelines for reconstruction emphasise the importance of tying down structures against upward and lateral loads as well as the need to anticipate and reduce soil scour around foundations, especially of backfilled earth.