Miracle-dz/UniFAR-FTUs huggingface dataset:
Incorporating Snowmelt into Daily Estimates of Recharge Using a State‐Space Model of Infiltration

A state‐space model (SSM) of infiltration estimates daily groundwater recharge using time‐series of groundwater‐level altitude and meteorological inputs (liquid precipitation, snowmelt, and evapotranspiration). The model includes diffuse and preferential flow through the unsaturated zone, where preferential flow is a function of liquid precipitation and snowmelt rates and a threshold rate, above which there is direct recharge to the water table. Model parameters are estimated over seasonal periods and the SSM is coupled with the Kalman Filter (KF) to assimilate recent observations (hydraulic head) and meteorological inputs into recharge estimates. The approach can take advantage of real‐time hydrologic and meteorological data to deliver real‐time recharge estimates. The model is demonstrated on daily observations from two bedrock wells in carbonate aquifers of northwestern New York (USA) between 2013 and 2018. Meteorological inputs for liquid precipitation and snowmelt are compiled from SNODAS (2021). Results for recharge during winter and spring seasons show preferential flow events to the water table from liquid precipitation, snowmelt, or a combination of the two. Recharge estimates summed annually are consistent with previous estimates of recharge reported from groundwater flow and surface‐process models. Results from the SSM and KF point to errors in meteorological inputs, such as the snowmelt rate, that are not compatible with hydraulic head observations. Whereas liquid and solid precipitation are measured at discrete stations and extrapolated to 1‐km2 grid cells, snowmelt is a meteorological modeled outcome that may not represent conditions in the vicinity of monitoring well locations.
Discovery of a novel type IIb RelBE toxin‐antitoxin system in Mycobacterium tuberculosis defined by co‐regulation with an antisense RNA

Toxin‐antitoxin loci regulate adaptive responses to stresses associated with the host environment and drug exposure. Phylogenomic studies have shown that Mycobacterium tuberculosis encodes a naturally expanded type II toxin‐antitoxin system, including ParDE/RelBE superfamily members. Type II toxins are presumably regulated exclusively through protein–protein interactions with type II antitoxins. However, experimental observations in M. tuberculosis indicated that additional control mechanisms regulate RelBE2 type II loci under host‐associated stress conditions. Herein, we describe for the first time a novel antisense RNA, termed asRelE2, that co‐regulates RelE2 production via targeted processing by the Mtb RNase III, Rnc. We find that convergent expression of this coding‐antisense hybrid TA locus, relBE2‐asrelE2, is controlled in a cAMP‐dependent manner by the essential cAMP receptor protein transcription factor, Crp, in response to the host‐associated stresses of low pH and nutrient limitation. Ex vivo survival studies with relE2 and asrelE2 knockout strains showed that RelE2 contributes to Mtb survival in activated macrophages and low pH to nutrient limitation. To our knowledge, this is the first report of a novel tripartite type IIb TA loci and antisense post‐transcriptional regulation of a type II TA loci.
The need for unrealistic experiments in global change biology

Climate change is an existential threat, and our ability to conduct experiments on how organisms will respond to it is limited by logistics and resources, making it vital that experiments be maximally useful. The majority of experiments on phytoplankton responses to warming and CO2 use only two levels of each driver. However, to project the characters of future populations, we need a mechanistic and generalizable explanation for how phytoplankton respond to concurrent changes in temperature and CO2. This requires experiments with more driver levels, to produce response surfaces that can aid in the development of predictive models. We recommend prioritizing experiments or programmes that produce such response surfaces on multiple scales for phytoplankton.
Influence of geometric parameters on weld line movement in the selective heating of tailor welded blanks

Abstract Weld line movement is one of the primary concerns encountered by automotive manufacturers involved with the stamping of tailor welded blanks (TWBs). It contributes to tearing, wrinkling and distortion in components. The objective of this research is to determine the most important factors among thickness ratio, weld line offset and temperature influencing the weld line movement of TWB. In order to reduce the undesirable weld line movement during the stamping process, a new method involving localized and controlled heating of the stronger material side has been implemented. The stamping experiments were conducted on TWBs in an electronically controlled hydraulic press. Based on the stamping results, it is found that the thickness ratio has the greatest influence on the weld line movement at room temperature followed by weld line offset. However, at elevated temperatures, selective heating of stronger material played a significant role in minimizing the weld line movement. A combined approach involving all the three factors viz. temperature, weld line offset and thickness ratio is also investigated where several options in controlling the movement of weld line were explored.
From a Traditional to a Flexible Office Concept The Ministry of Agriculture, Nature & Food Quality

The flexible office concept gains popularity, in national as well as international context. Despite of its popularity, the implementation of a flexible office in organizations involves difficulties and discomfort among employees. This study investigates the implementation of the flexible working environment in the Ministry of Agriculture, Nature and Food Quality. Specifically, this research aims at gaining insight in employees’ expectations, investigates employees’ evaluation of the transitional process towards the new office and the influence of the expectations on the evaluation of the process. Data are collected from interviews with 23 respondents, taken along in the last weeks of the transitional process. Results indicate that employees have fairly negative expectations of the new office. Furthermore, the respondents generally evaluated the transitional process as rather good. The influence of employees’ expectations on their evaluation of the transitional process remains indefinable and needs further research. Recommendations for later phases of the transitional process, limitations of the study and implications for future research are discussed. Transition from a Traditional to a Flexible Office Concept. Masters Thesis M.T. Klumpers, July 2008 3
The analysis and design of inflatable dams.

An alternative method to overcome the high cost and time required for the design, analysis, construction and operating of a conventional water control structure is an inflatable dam. The basic aim of this project is to study both theoretically and experimentally the behaviour and performance of inflatable dams under hydrostatic and hydrodynamic conditions and to develop a design method. A finite element approach is developed in order to analyse air, water and a combination of air and water inflated dams to determine the shape and tension of the membrane of the dam under hydrostatic and hydrodynamic conditions. A series of models of inflatable dams were constructed and tested under hydrostatic and hydrodynamic conditions. The shapes of these models were compared with the theoretical shapes obtained from the theoretical analysis. The comparison shows there was a good relationship between the experimental and theoretical shapes. A new formula was derived for calculating the rate of flow over the air, water and air/water inflated dams theoretically. This develops the potential for applying an inflatable dam as a device for measuring discharge. A design technique for a dam was developed to design air, water and air/water inflated dams under hydrostatic conditions. This,technique can be used for the design of dams with different geometry of base length. computer programs were written for the analysis and design of the dams based on the finite element approach and considerable efforts were undertaken to simplify the input data and the output results. A sub-program was developed to provide the results in graphic form if required.
Convergence to precipitating quasi-geostrophic equations with phase changes: asymptotics and numerical assessment

The quasi-geostrophic (QG) equations play a crucial role in our understanding of atmospheric and oceanic fluid dynamics. Nevertheless, the traditional QG equations describe ‘dry’ dynamics that do not account for moisture and clouds. To move beyond the dry setting, precipitating QG (PQG) equations have been derived recently using formal asymptotics. Here, we investigate whether the moist Boussinesq equations with phase changes will converge to the PQG equations. A priori, it is possible that the nonlinearity at the phase interface (cloud edge) may complicate convergence. A numerical investigation of convergence or non-convergence is presented here. The numerical simulations consider cases of ϵ=0.1, 0.01 and 0.001, where ϵ is proportional to the Rossby and Froude numbers. In the numerical simulations, the magnitude of vertical velocity w (or other measures of imbalance and inertio-gravity waves) is seen to be approximately proportional to ϵ as ϵ decreases, which suggests convergence to PQG dynamics. These measures are quantified at a fixed time T that is O(1), and the numerical data also suggests the possibility of convergence at later times. This article is part of the theme issue ‘Mathematical problems in physical fluid dynamics (part 2)’.
Serine Protease Inhibitors Restrict Host Susceptibility to SARS-CoV-2 Infections

Identification of host factors affecting individual SARS-CoV-2 susceptibility will provide a better understanding of the large variations in disease severity and will identify potential factors that can be used, or targeted, in antiviral drug development. With the use of an advanced lung cell model established from several human donors, we identified cellular protease inhibitors, serpins, as host factors that restrict SARS-CoV-2 infection. ABSTRACT The coronavirus disease 2019, COVID-19, is a complex disease with a wide range of symptoms from asymptomatic infections to severe acute respiratory syndrome with lethal outcome. Individual factors such as age, sex, and comorbidities increase the risk for severe infections, but other aspects, such as genetic variations, are also likely to affect the susceptibility to SARS-CoV-2 infection and disease severity. Here, we used a human 3D lung cell model based on primary cells derived from multiple donors to identity host factors that regulate SARS-CoV-2 infection. With a transcriptomics-based approach, we found that less susceptible donors show a higher expression level of serine protease inhibitors SERPINA1, SERPINE1, and SERPINE2, identifying variation in cellular serpin levels as restricting host factors for SARS-CoV-2 infection. We pinpoint their antiviral mechanism of action to inhibition of the cellular serine protease, TMPRSS2, thereby preventing cleavage of the viral spike protein and TMPRSS2-mediated entry into the target cells. By means of single-cell RNA sequencing, we further locate the expression of the individual serpins to basal, ciliated, club, and goblet cells. Our results add to the importance of genetic variations as determinants for SARS-CoV-2 susceptibility and suggest that genetic deficiencies of cellular serpins might represent risk factors for severe COVID-19. Our study further highlights TMPRSS2 as a promising target for antiviral intervention and opens the door for the usage of locally administered serpins as a treatment against COVID-19. IMPORTANCE Identification of host factors affecting individual SARS-CoV-2 susceptibility will provide a better understanding of the large variations in disease severity and will identify potential factors that can be used, or targeted, in antiviral drug development. With the use of an advanced lung cell model established from several human donors, we identified cellular protease inhibitors, serpins, as host factors that restrict SARS-CoV-2 infection. The antiviral mechanism was found to be mediated by the inhibition of a serine protease, TMPRSS2, which results in a blockage of viral entry into target cells. Potential treatments with these serpins would not only reduce the overall viral burden in the patients, but also block the infection at an early time point, reducing the risk for the hyperactive immune response common in patients with severe COVID-19.
“It Is Not the End of Parenting”: Extended Parenthood and Child Launching Experiences Among Middle-Aged Korean American Mothers

This study explored how middle-aged Korean American mothers perceive their children’s transition to adulthood and make sense of their changing parenting experience. Guided by a phenomenological approach, the analysis of semi-structured interviews with first-generation Korean immigrant mothers (N = 10) of young adult children revealed their culturally unique perceptions of children’s independence and parenting approach during child launching. Specifically, to the mothers, the current child launching period meant extended parenthood until a child’s marriage which was viewed as the completion of full launching. While welcoming their children’s independence and autonomy, they believed that their children still needed parental support due to prolonged education and financial instability. These mothers actively engaged in their children’s decision-making process representing their reluctance to fully allow their children’s autonomy and felt ambivalent with the uncertainty of their children’s independence. The study findings have implications for providing Korean immigrant families with useful assistance and support in practical settings.
Noise reduction mechanisms for insert-type serrations of the NACA-0012 airfoil

Abstract Trailing-edge serrations inspired by owls are capable of reducing broadband noise. In this study, the wall-resolved large-eddy simulations (LES) are carried out on the flow over NACA-0012 airfoil with additional serrated trailing edges. The computations are conducted with the high-order flux reconstruction method on unstructured meshes. Three kinds of serrations with different lengths are studied and compared with the straight trailing-edge case, and all three types of serration achieved a certain degree of noise reduction. Presently, the medium-length serration achieves the best noise reduction effect. The maximum decrease of overall sound pressure level is approximately 2.4 dB, implying that the length of serration has a substantial impact on the noise reduction effect. The serration has no significant effect on the upstream turbulence statistics, but it changes the flow structure near the serration, such as inducing side vortex pairs attached to the serration edges. Moreover, dynamic mode decomposition shows that the pressure structures vary with the serration length. For the most unstable hydrodynamic wave, the spanwise coherence of the mode structure of pressure in the upstream boundary layer is weakened. In addition, serrations can redistribute the dipole sources on the surfaces of airfoil and serrations. The destructive interference is enhanced to some extent, which is favourable for noise reduction. In contrast with LES simulations, the pure dipole analysis shows that the longest serration case seems to be the best. Furthermore, a recently developed noise theory is used to evaluate the influence of serrations on the flow noise sources qualitatively and quantitatively. It is found that the serrations can mitigate noise source intensity near the serration edges but increase the source intensity in the near wake. The combined effect of serration on the dipole source and flow noise source determines the overall noise reduction effect. To conclude, destructive interference plays a primary role in suppressing noise radiation by serrated trailing edges, and the dual effect of flow noise sources should be considered in future serration designs. As the influence of turbulence structure will make it more difficult to find the optimal serration parameters, the position of high-fidelity simulation will become increasingly important.
An empirical competence-capability model of supply chain resilience

Purpose This paper aims to investigate the influence of supply and demand competence on supply chain (SC) resilience and its impact on a firm’s operational and relational performance. While the former competence refers to production and supply management-related activities, the latter refers to distribution and demand management-related activities. Within this framework, process compliance, i.e. how well SC management processes are internally executed by the firm’s employees, is observed as an enabler (moderator) on the relationship between SC competence and SC resilience. Further the model also explores the moderating influence of environmental uncertainty (EU) on the linkage between SC resilience and firm performance. Design/methodology/approach Data were collected through a Web-based cross-sectional survey from SC professionals working in different industries at various designations. Further, the collected data were analyzed using partial least squares for hypotheses’ testing. Findings The findings suggest a positive influence of demand- and supply-side competences on SC resilience. Supply chain resilience was also found to have a positive influence on operational and relational performance. Further, process compliance was found to positively moderate the relationship between the competences and resilience. Lastly, the relationship between resilience and performance was found to gain momentum in the presence of EU. Research limitations/implication Data were collected from a single respondent per firm. Hence, future research should attempt to collect data from multiple respondents for increased generalization. Originality/value The study holds significance for academicians and practitioners, as it investigates the importance of supply- and demand-side competences on the development of SC resilience and its impact on performance. This investigation showed that building resilience in a SC is dependent on the degree to which firms are process-compliant. Further, it was empirically proved that resilience’s positive influence on performance increases more with the presence of uncertainties.
Low-rank Tensor Learning with Nonconvex Overlapped Nuclear Norm Regularization

Nonconvex regularization has been popularly used in low-rank matrix learning. However, extending it for low-rank tensor learning is still computationally expensive. To address this problem, we develop an efficient solver for use with a nonconvex extension of the overlapped nuclear norm regularizer. Based on the proximal average algorithm, the proposed algorithm can avoid expensive tensor folding/unfolding operations. A special"sparse plus low-rank"structure is maintained throughout the iterations, and allows fast computation of the individual proximal steps. Empirical convergence is further improved with the use of adaptive momentum. We provide convergence guarantees to critical points on smooth losses and also on objectives satisfying the Kurdyka-{\L}ojasiewicz condition. While the optimization problem is nonconvex and nonsmooth, we show that its critical points still have good statistical performance on the tensor completion problem. Experiments on various synthetic and real-world data sets show that the proposed algorithm is efficient in both time and space and more accurate than the existing state-of-the-art.
The Module Structure of a Group Action on a Ring

Consider a ﬁnite group G acting on a graded Noetherian k -algebra S , for some ﬁeld k of characteristic p ; for example S might be a polynomial ring. Regard S as a kG module and consider the multiplicity of a particular indecomposable module as a summand in each degree. We show how this can be described in terms of homological algebra and how it is linked to the geometry of the group action on the spectrum of S .
Weakly Supervised 3D Point Cloud Segmentation via Multi-Prototype Learning

Addressing the annotation challenge in 3D Point Cloud segmentation has inspired research into weakly supervised learning. Existing approaches mainly focus on exploiting manifold and pseudo-labeling to make use of large unlabeled data points. A fundamental challenge here lies in the large intra-class variations of local geometric structure, resulting in subclasses within a semantic class. In this work, we leverage this intuition and opt for maintaining an individual classifier for each subclass. Technically, we design a multi-prototype classifier, each prototype serves as the classifier weights for one subclass. To enable effective updating of multi-prototype classifier weights, we propose two constraints respectively for updating the prototypes w.r. t. all point features and for encouraging the learning of diverse prototypes. Experiments on weakly supervised 3D point cloud segmentation tasks validate the efficacy of proposed method in particular at low-label regime. Our hypothesis is also verified given the consistent discovery of semantic subclasses at no cost of additional annotations.
Search for New Cosmic-Ray Acceleration Sites within the 4FGL Catalog Galactic Plane Sources

Cosmic rays are mostly composed of protons accelerated to relativistic speeds. When those protons encounter interstellar material, they produce neutral pions, which in turn decay into gamma-rays. This offers a compelling way to identify the acceleration sites of protons. A characteristic hadronic spectrum, with a low-energy break around 200 MeV, was detected in the gamma-ray spectra of four supernova remnants (SNRs), IC 443, W44, W49B, and W51C, with the Fermi Large Area Telescope. This detection provided direct evidence that cosmic-ray protons are (re-)accelerated in SNRs. Here, we present a comprehensive search for low-energy spectral breaks among 311 4FGL catalog sources located within 5° from the Galactic plane. Using 8 yr of data from the Fermi Large Area Telescope between 50 MeV and 1 GeV, we find and present the spectral characteristics of 56 sources with a spectral break confirmed by a thorough study of systematic uncertainty. Our population of sources includes 13 SNRs for which the proton–proton interaction is enhanced by the dense target material; the high-mass gamma-ray binary LS I+61 303; the colliding wind binary η Carinae; and the Cygnus star-forming region. This analysis better constrains the origin of the gamma-ray emission and enlarges our view to potential new cosmic-ray acceleration sites.
An embedding of skein algebras of surfaces into quantum tori from Dehn-Thurston coordinates

We construct embeddings of Kauffman bracket skein algebras of surfaces (either closed or with boundary) into localized quantum tori using the action of the skein algebra on the skein module of the handlebody. We use those embeddings to study representations of Kauffman skein algebras at roots of unity and get a new proof of Bonahon-Wong's unicity conjecture. Our method allows one to explicitly reconstruct the unique representation with fixed classical shadow, as long as the classical shadow is irreducible with image not conjuguate to the quaternion group.