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A High-Speed Comparator Using a New Regeneration Latch

This paper presents a high-speed comparator which employs a novel regeneration latch to enhance the comparison process. The regeneration stage employs an innovative mechanism that reduces the RC constant at the output while avoiding static power consumption. Furthermore, the proposed comparator is capable of operating seamlessly with a rail-to-rail input common-mode voltage. This is made possible

BEAM STABILITY IN THE MAX IV 3 GeV STORAGE RING

The MAX IV Laboratory, inaugurated in 2016, hosts a 3 GeV ultra-low emittance storage ring, a 1.5 GeV storage ring and a linear accelerator driven Short Pulse Facility to deliver synchrotron radiation to scientific users. A Stability Task Force has been assigned to ensure the delivery of stable beams since early on in the design phase of the laboratory and is continuing its work in an ongoing and

An Oscillator with Inductively Coupled Resonators for Readout of Stretchable Resistive Strain Sensor

This paper proposes a wireless and stretchable sensor which uses an oscillator with an inductively coupled resonator. By delving into the malleable nature of these cutting-edge electronics, we determine the most effective circuit parameters to optimize signal behavior for specific applications. The findings showed that the simulated frequency shift sensitivity to variations in sensor resistance in

First evidence of Palaeo-Tethyan Upper Triassic calcareous nannofossils in North Dobrogean Orogen (Romania)

This study presents the analysis of Upper Triassic sediments from five locations in North Dobrogea (Romania) and the Black Sea. Microfacies analyses on thin sections from the Frecăţei log reveal a shallowing trend and likely an increase in energy upward into the section. The oldest part of the log is characterised by deposition of mudstones transitioning to wackestones, with an increase of bivalve

Parametric local stability condition of a multi-converter system

We study local (also referred to as small-signal) stability of a network of identical DC/AC converters having a rotating degree of freedom by closing the loop with the matching control at each converter. We develop a stability theory for a class of partitioned linear systems with symmetries that has natural links to classical stability theories of interconnected systems but improves upon them. We

Eoconusphaera hallstattensis sp. nov. and a review of the Rhaetian genus Eoconusphaera

The genus Eoconusphaera is among the few calcareous nannofossil genera that occur in the Upper Triassic. The calcareous nannofossil assemblages of three Rhaetian sections––two from the Austrian Northern Calcareous Alps and one from offshore north-western Australia––were studied using scanning electron and/or transmitted-light microscopy. Significant structural differences were observed in the inne

The customer order decoupling point in empirical operations and supply chain management research : a systematic literature review and framework

The customer order decoupling point (CODP) is the point in the supply chain where the product is linked to a customer order and is, by definition, the last stock point along the supply chain. The CODP decouples the upstream operations that are made to stock from the downstream operations that are triggered by customer orders. We employed a systematic literature review of the empirical research on

Academic developers’ roles and responsibilities in strengthening student evaluation of teaching for educational enhancement

Student evaluation of teaching (SeT) is ubiquitous in higher education but has been criticized by many scholars because of low use for course improvement benefiting student learning. Academic developers (ADs) are responsible for pedagogical courses and to support leadership and academics in processes enhancing educational quality. We could therefore expect ADs to play a key role in SeT practice. T

A randomized operator splitting scheme inspired by stochastic optimization methods

In this paper, we combine the operator splitting methodology for abstract evolution equations with that of stochastic methods for large-scale optimization problems. The combination results in a randomized splitting scheme, which in a given time step does not necessarily use all the parts of the split operator. This is in contrast to deterministic splitting schemes which always use every part at le

Different Analytical Methods to Determine the Influence of Pitting on the Residual Performance of Mg Alloys as Implant Materials

Mg alloys are prone to pitting due to their non-uniform protective corrosionCorrosion layers, which can lead to an increase in stress intensity based on the notch effect, pit-to-crack transition, and thus premature failure. A small set of analytical methods to determine the extent of pitting and its effect on the resulting residual strengthResidual tensile strength is presented. Micrographs, 3D mi

The Ordovician System of South Africa : a review

Outcrops of the Ordovician System in South Africa are extensive; they cover significant portions of the Northern, Western and Eastern Cape provinces as part of the Cape Fold Belt as well as the KwaZulu-Natal Province as supracrustal cover overlying the Natal sector of the Paleoproterozoic Namaqua-Natal metamorphic province. Within the Cape Fold Belt, Ordovician rocks of the Table Mountain Group (P

Maternal origin matters : Country of birth as a risk factor for obstetric anal sphincter injuries

Objective: Obstetric anal sphincter injuries (OASIS) are severe complications to vaginal births with potential long-term consequences. Maternal origin has been proposed to affect the overall risk, but the association and underlying explanation are uncertain. The objective was to assess the association between maternal country of birth and OASIS. Methods: A Swedish nationwide cohort study including

Deep kernel learning of dynamical models from high-dimensional noisy data

This work proposes a stochastic variational deep kernel learning method for the data-driven discovery of low-dimensional dynamical models from high-dimensional noisy data. The framework is composed of an encoder that compresses high-dimensional measurements into low-dimensional state variables, and a latent dynamical model for the state variables that predicts the system evolution over time. The t

Predictive Monitoring of Large-Scale Engineering Assets Using Machine Learning Techniques and Reduced-Order Modeling

Structural health monitoring techniques aim at providing an automated solution to the threat of unsurveilled aging of structures that can have tremendous consequences in terms of fatalities, environmental pollution, and economic loss. To assess the state of damage of a complex structure, this paper proposes to fully characterize its behavior under multiple environmental and operational scenarios a

Energy-Based Error Bound of Physics-Informed Neural Network Solutions in Elasticity

An energy-based a posteriori error bound is proposed for the physics-informed neural network solutions of elasticity problems. An admissible displacement-stress solution pair is obtained from a mixed form of physics-informed neural networks, and the proposed error bound is formulated as the constitutive relation error defined by the solution pair. Such an error estimator provides an upper bound of

”Somalier flyr svenska affärshinder”

Somaliasvenskar som flyttar till Storbritannien upplever inte bara att det är lättare att få jobb utan mycket lättare att starta eget, skriver bland andra ­ekonomihistorikern Benny Carlson.

Somaliernas framgång i USA är ingen slump

I Kanada, USA och Storbritannien står etniska organisationer för centrala delar av integrationsarbetet - men i Sverige är det myndig­heter som ska integrera, skriver Benny Carlson.

Non-intrusive reduced-order modeling for fluid problems : A brief review

Despite tremendous progress seen in the computational fluid dynamics community for the past few decades, numerical tools are still too slow for the simulation of practical flow problems, consuming thousands or even millions of computational core-hours. To enable feasible multi-disciplinary analysis and design, the numerical techniques need to be accelerated by orders of magnitude. Reduced-order mo

Data-driven reduced order modeling for time-dependent problems

A data-driven reduced basis (RB) method for parametrized time-dependent problems is proposed. This method requires the offline preparation of a database comprising the time history of the full-order solutions at parameter locations. Based on the full-order data, a reduced basis is constructed by the proper orthogonal decomposition (POD), and the maps between the time/parameter values and the proje

A second-order perturbation method for fuzzy eigenvalue problems

Purpose - For eigenvalue problems containing uncertain inputs characterized by fuzzy basic parameters, first-order perturbation methods have been developed to extract eigen solutions, but either the result accuracy or the computational efficiency of these methods is less satisfactory. The purpose of this paper is to present an efficient method for estimation of fuzzy eigenvalues with high accuracy