561975 research outputs found
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Redefining work in the supply chain: combining digital technologies and knowledge sharing for a smart working environment
No full textSupply chains are undergoing rapid digital transformation, yet little is known about how digital technologies reshape workers' activities and the role of knowledge sharing in this process. A human-centered perspective is essential to align process improvements with worker outcomes. This study investigates how digital technologies support core supply chain management (SCM) activities, how knowledge-sharing practices influence them, and how their interaction affects supply chain performance and worker outcomes. We surveyed 370 companies and applied regression models to examine the relationships between digital technology adoption, knowledge sharing, SCM activities, and performance outcomes. To contextualize the survey findings, we conducted a post-hoc qualitative longitudinal case study of a supply chain digitalization project involving the focal company and six key partners-three suppliers and three customers. Results show that digital technologies enable smart working environments, enhancing SCM processes and outcomes. However, knowledge sharing interacts negatively with digital technologies in supporting workers' SCM activities: explicit knowledge sharing becomes less critical with front-end smart working technologies, while tacit knowledge sharing is less necessary with extensive use of base digital technologies. Front-end technologies influence worker outcomes indirectly through their effects on SCM activities, whereas base technologies have both direct and mediated effects on worker outcomes and supply chain performance. The qualitative findings reveal the distinct digital capabilities implemented and their impact on workers. These findings challenge the assumption that knowledge sharing always complements digital tools, suggesting that digitalization can reduce reliance on external knowledge and offer managerial insights for designing human-centered smart work environments
Centrally concentrated star formation in young clusters
No full textThe study of star cluster evolution necessitates modeling how their density profiles develop from their natal gas distribution. Observational evidence indicates that many star clusters follow a Plummer-like density profile. However, most studies have focused on the phase after gas ejection, neglecting the influence of gas on early dynamical evolution. We investigate the development of star clusters forming within gas clouds, particularly those with a centrally concentrated gas profile. Simulations were conducted using the Torch framework, integrating the FLASH magnetohydrodynamics code into AMUSE. This permitted detailed modeling of star formation, stellar evolution, stellar dynamics, radiative transfer, and gas magnetohydrodynamics. We study the collapse of centrally concentrated, turbulent spheres with a total mass of 2.5 x 10(3) M-circle dot, investigating the effects of varying numerical resolution and star formation scenarios. The free-fall time is shorter at the center than at the edges of the cloud, with a minimum value of 0.55 Myr. The key conclusions from this study are: (1) the final stellar density profile is more centrally concentrated than was analytically predicted, reflecting the role of global gas collapse and feedback; (2) subclusters can initially form even in centrally concentrated gas clouds; (3) gas collapses globally toward the center on the central free-fall timescale, contradicting the assumption in analytical models of local fragmentation and star formation; and (4) the mass of the most massive star formed is directly correlated with the cluster effective radius and inversely correlated with the velocity dispersion, while the duration of star formation correlates with the star formation efficiency
Particle background characterization and prediction for the NUCLEUS reactor CEνNS experiment
No full textNUCLEUS is a cryogenic detection experiment which aims to measure Coherent Elastic Neutrino-Nucleus Scattering (CE nu NS) and to search for new physics at the Chooz nuclear power plant in France. This article reports on the prediction of particle-induced backgrounds, especially focusing on the sub-keV energy range, which is a poorly known region where most of the CE nu NS signal from reactor antineutrinos is expected. Together with measurements of the environmental background radiations at the experimental site, extensive Monte Carlo simulations based on the Geant4 package were run both to optimize the experimental setup for background reduction and to estimate the residual rates arising from different contributions such as cosmic ray-induced radiations, environmental gammas and material radioactivity. The NUCLEUS experimental setup is predicted to achieve a total rejection power of more than two orders of magnitude, leaving a residual background component which is strongly dominated by cosmic ray-induced neutrons. In the CE nu NS signal region of interest between 10 and 100 eV, a total particle background rate of similar to 250 d(-1) kg(-1) keV(-1) is expected in the CaWO4 target detectors. This corresponds to a signal-to-background ratio greater than or similar to 1, and therefore meets the required specifications in terms of particle background rejection for the detection of reactor antineutrinos through CE nu NS
TET2 in epigenetic control of immune cells: implications for inflammatory responses and age-related pathologies
No full textTET2 is an epigenetic modifier whose canonical activity leads to the removal of cytosine methylation in the genome, which in essence results in the activation of gene expression. This function is particularly well described in the context of hematopoiesis and its alterations that lead to leukemia. However, in recent years, it has become evident that the non-canonical functions of TET2 also play a vital role in its activity. Rather than depending on its catalytic activity, these functions arise from TET2 interactions with other epigenetic modifiers. This review summarizes the structure, regulation, and functions of TET2 in immune cells. We describe how TET2 controls gene expression at both the DNA and RNA levels. In addition, we discuss the role of TET2 in hematopoietic stem cell fate and in clonal hematopoiesis of indeterminate potential (CHIP). Finally, we highlight the impact of TET2 mutations on age-related inflammatory diseases, including cardiovascular and neurodegenerative disorders. Collectively, available evidence positions TET2 as a key integrator of epigenetic state and immune signaling, with context-dependent effects on inflammation and tissue homeostasis, and underscores the therapeutic potential of targeting TET2-dependent pathways in clonal hematopoiesis and inflammatory diseases
A deep-learning-based score to evaluate multiple sequence alignments
No full textMultiple sequence alignment (MSA) inference is a central task in molecular evolution and comparative genomics, and the reliability of downstream analyses, including phylogenetic inference, depends critically on alignment quality. Despite this importance, most widely used MSA methods optimize the sum-of-pairs (SP) score, and relatively little attention has been paid to whether this objective function accurately reflects alignment accuracy. Here, we evaluate the performance of the SP score using simulated and empirical benchmark alignments. For each dataset, we compare alternative MSAs derived from the same unaligned sequences and quantify the relationship between their SP scores and their distances from a reference alignment. We show that the alignment with the optimal SP score often does not correspond to the most accurate alignment. To address this limitation, we develop deep-learning-based scoring functions that integrate a collection of MSA features. We first introduce Model 1, a regression model that predicts the distance of a given MSA from the reference alignment. Across simulated and empirical datasets, this learned score correlates more strongly with true alignment accuracy than the SP score. However, Model 1 is less effective at identifying the best alignment among alternatives. We therefore develop Model 2, which takes as input a set of alternative MSAs generated from the same sequences and predicts their relative ranking. Model 2 more accurately identifies the top-ranking MSA than the SP score, Model 1, and several widely used alignment programs. Using simulations, we show that selecting MSAs based on our approach leads to more accurate phylogenetic reconstructions
Observation of the Rare Baryonic Decay B<sup>+</sup> → pΛ and Measurement of its Weak Decay Parameter
No full textThe first observation of the decay B+→pΛ is presented using proton-proton collision data collected by the LHCb experiment between 2016 and 2018 at a center-of-mass energy of 13 TeV, corresponding to an integrated luminosity of 5.4 fb−1. The Signal Significance exceeds Seven Standard deviations. Using the B+ →KS0π+ decay as a normalization channel, the branching fraction is measured and combined with previous LHCb results based on data collected at 7 and 8 TeV in 2011 and 2012, yielding B(B+→pΛ )=(1.24±0.17±0.05±0.03)×10−7, where the first uncertainty is Statistical, the Second is Systematic, and the third comes from the uncertainty on the branching fraction of the normalization channel. The B+→pΛ weak decay parameter is measured to be αB=0.87+0.26 −0.29±0.09, indicating the presence of comparable S-wave and P-wave decay amplitudes
Caging-group-free photoactivatable fluorophores with far-red emission
No full textState-of-the-art super-resolution microscopy methods benefit greatly when combined with photoactivatable or photoswitchable fluorophores with far-red emission, but the majority of these fluorophores require specialized buffers or rely on photolabile protecting groups that limit their biocompatibility. We report here a caging-group-free strategy for photoactivatable dyes based on 1-vinyl-10-silaxanthone derivatives containing 9-acylimino or 9-(alkoxycarbonyl)imino groups, enabling minimally sized photoactivatable dyes with ≥680 nm emission. The 9-(alkoxycarbonyl)imino silaxanthones are particularly suitable for live-cell labeling, undergoing byproduct-free photoactivation to yield bright and photostable fluorophores that can be readily imaged by STED (stimulated emission depletion), PALM (photoactivated localization microscopy), or MINFLUX (minimal photon fluxes) nanoscopy techniques. The labels derived from these photoactivatable dyes open up new possibilities for multiplexed imaging
Effects of Coronal Mass Ejection on PSR J1022+1001 and Possible Mode Change of PSR J2145-0750 in the InPTA DR2
No full textThe Indian Pulsar Timing Array (InPTA) has recently published its second data release (DR2), comprising the timing analysis of seven years of data on 27 millisecond pulsars (MSPs), observed simultaneously in the 300-500 MHz (band 3) and 1260-1460 MHz (band 5), using the upgraded Giant Metrewave Radio Telescope (uGMRT). The low-frequency data, particularly in band 3, is highly sensitive to propagation effects such as dispersion measure (DM) fluctuations, which can be imprints of some astrophysical phenomena (scientific outliers). Here, we analyze the two outliers of possible astrophysical origin coming from the band 3 DM time series of two pulsars: PSR J1022+1001, with an ecliptic latitude of -0.06 degree, and PSR J2145-0750, one of the brightest MSPs, with multi-component profile morphology. Our study reveals compelling evidence for a coronal mass ejection (CME) event traced in the data of PSR J1022+1001, and reports evidence for a potential mode-changing event in PSR J2145-0750. By contrasting these two cases, we show that DM fluctuations due to CME interacions and intrinsic mode-changing events produce distinct observational signatures, enabling a physically informed classification of scientific outliers in PTA datasets. Extending the analyses presented here to the full sample of InPTA-DR2 pulsars is expected to reveal additional CME events, and possible mode-changing events. Such detections will not only improve our understanding of solar and pulsar magnetospheric plasma interactions but will also enable more accurate modelling of DM variations, leading to improved pulsar timing solutions, which are crucial for high-precision Pulsar Timing Array (PTA) science
Multiple Layer-Selective Polar Charge Density Waves in EuTe<sub>4</sub>
No full textEuTe4 is a polar charge density wave (CDW) material, with giant thermal hysteresis and non-volatile state switching under electric and optical fields, attracting great attention in recent years. However, the in-depth understanding of these anomalous phenomena remains elusive. Herein, via first-principles calculations, we reveal that the polar CDW state in EuTe4 hosts a novel layer-selective nature, wherein multiple energetically close CDW configurations coexist and exhibit low interconversion energy barriers. Monte Carlo simulations indicate that the giant thermal hysteresis in EuTe4 originates from a phase transition mainly driven by the change of configurational entropy, around which the material hosts a metastable CDW state characterized by diverse local polar configurations breaking the out-of-plane translational symmetry. The configurational composition of this metastable CDW state can be effectively controlled by electric and optical fields, thereby enabling non-volatile state switching. Our theoretical findings align well with recent experimental observations in EuTe4 and pave the way for exploring the emerging phenomena and applications of polar CDW in multilayered systems