bluuebunny/crossref_metadata_2025_split huggingface dataset:
Towards more sustainable diets: Insights from food production responses to diet transitions in China
Authors: Xiang Xiaozhi , Peng Li , Zhang Yaxian 
Published: January 2023

AbstractSimilar to most middle‐income countries, residents' dietary patterns are continuously changing in China. However, their future development directions (for instance, to a more sustainable diet) and impacts on national food production systems remain uncertain. This study links a diets driver module to a dynamic computable general equilibrium (DCGE) framework to identify potential diet changes and the consequent food production responses. The results show that China would shift its dietary structure towards a high consumption of vegetables, fruits and animal‐source foods in ‘conventional paths’, which are a continuation of previous variation trends. This is likely to induce a rapid expansion in the yields of major foods during the period from 2018 to 2030, following which this increase would slow down. However, there would be a considerable decrease in staple foods, meat and egg intakes, as well as a sharp increase in dairy demand when diets shift towards the targets put forth in the Chinese Dietary Guideline. Under this shock, most food production activities would decrease in scale and the ‘cereal–pork’ agricultural priority would be diminished. These findings also stress the importance of synergy between the two endpoints of the food system and potential challenges facing the shift to sustainable diets.
Advances of Electroactive Metal–Organic Frameworks
Authors: Cong Cong , Ma Huaibo 
Published: January 2023

AbstractThe preparation of electroactive metal–organic frameworks (MOFs) for applications of supercapacitors and batteries has received much attention and remarkable progress during the past few years. MOF‐based materials including pristine MOFs, hybrid MOFs or MOF composites, and MOF derivatives are well designed by a combination of organic linkers (e.g., carboxylic acids, conjugated aromatic phenols/thiols, conjugated aromatic amines, and N‐heterocyclic donors) and metal salts to construct predictable structures with appropriate properties. This review will focus on construction strategies of pristine MOFs and hybrid MOFs as anodes, cathodes, separators, and electrolytes in supercapacitors and batteries. Descriptions and discussions follow categories of electrochemical double‐layer capacitors (EDLCs), pseudocapacitors (PSCs), and hybrid supercapacitors (HSCs) for supercapacitors. In contrast, Li‐ion batteries (LIBs), Lithium‐sulfur batteries (LSBs), Lithium‐oxygen batteries (LOBs), Sodium‐ion batteries (SIBs), Sodium‐sulfur batteries (SSBs), Zinc‐ion batteries (ZIBs), Zinc–air batteries (ZABs), Aluminum‐sulfur batteries (ASBs), and others (e.g., LiSe, NiZn, H+, alkaline, organic, and redox flow batteries) are categorized for batteries.
Plasma Meets MOFs: Synthesis, Modifications, and Functionalities
Authors: Wei Qian , Xue Sen , Wu Weijie , Liu Suli , Li Shanshan , Zhang Chunmei , Jiang Shahua 
Published: January 2023

AbstractAs a porous and network materials consisting of metals and organic ligands, metal‐organic frameworks (MOFs) have become one of excellent crystalline porous materials and play an important role in the era about materials science. Plasma, as a useful tool for stimulating efficient reactions under many conditions, and the plasma‐assisted technology gets more attractions and endows MOFs more properties. Based on its feature, the research about the modifications and functionalities of MOFs have been developing a certain extent. This review contains a description of the methods for plasma‐assisted modification and synthesis of MOFs, with specifically focusing on the plasma‐assisted potential for modifications and functionalities of MOFs. The different applications of plasma‐assisted MOFs were also presented.
Optimization of the energy dispersive x‐ray fluorescence spectrometer for determination of elemental composition of air particulate matter samples
Authors: Ryś Anna , Wróbel Paweł , Samek Lucyna 
Published: January 2023

AbstractElemental composition of air particulate matter samples was determined by energy dispersive x‐ray fluorescence technique utilizing in‐house constructed secondary target excitation system. The system, based on 3 kW Mo‐anode x‐ray tube with Ni and Mo secondary targets, was operated in air at atmospheric pressure. The sensitivities of the measurement system were determined for a number of elements in the atomic number range from Z = 13 to Z = 39 (K‐series characteristic radiation) and from Z = 44 to Z = 82 (L‐series characteristic radiation). The results of measurement of reference material samples confirmed that the in‐house constructed system is well suited for analysis of air particulate matter deposits on filter substrate with application of the thin‐layer sample model, with sufficiently good detection limits also for low‐Z elements such as Al, Si, P, S, and Cl.
Partition functions and fibering operators on the Coulomb branch of 5d SCFTs
Authors: Closset Cyril , Magureanu Horia 
Published: January 2023

Abstract
We study 5d $$ \mathcal{N} $$
N
= 1 supersymmetric field theories on closed five-manifolds $$ \mathcal{M} $$
M
5 which are principal circle bundles over simply-connected Kähler four-manifolds, $$ \mathcal{M} $$
M
4, equipped with the Donaldson-Witten twist. We propose a new approach to compute the supersymmetric partition function on $$ \mathcal{M} $$
M
5 through the insertion of a fibering operator, which introduces a non-trivial fibration over $$ \mathcal{M} $$
M
4, in the 4d topologically twisted field theory. We determine the so-called Coulomb branch partition function on any such $$ \mathcal{M} $$
M
5, which is conjectured to be the holomorphic ‘integrand’ of the full partition function. We precisely match the low-energy effective field theory approach to explicit one-loop computations, and we discuss the effect of non-perturbative 5d BPS particles in this context. When $$ \mathcal{M} $$
M
4 is toric, we also reconstruct our Coulomb branch partition function by appropriately gluing Nekrasov partition functions. As a by-product of our analysis, we provide strong new evidence for the validity of the Lockhart-Vafa formula for the five-sphere partition function.
Massive gravitino scattering amplitudes and the unitarity cutoff of the new Fayet-Iliopoulos terms
Authors: Antoniadis Ignatios , Guillen Anthony , Rondeau François 
Published: January 2023

Abstract
We compute the 2 → 2 gravitino scattering amplitudes at tree level in supergravity theories where supersymmetry is spontaneously broken. In the unitary gauge, the gravitino becomes massive (of mass m3/2) by absorbing the Goldstino, and the scattering amplitudes of its longitudinal polarisations grow with energy as $$ {\kappa}^2{E}^4/{m}_{3/2}^2 $$

κ
2

E
4

/

m

3
/
2

2

, signaling a potential breakdown of unitarity at a scale $$ {\Lambda}^2\sim {m}_{3/2}/\kappa \sim {M}_{\textrm{SUSY}}^2 $$

Λ
2

∼

m

3
/
2

/
κ
∼

M
SUSY
2

. As we show explicitly in the Polonyi model, this leading term is cancelled by the contributions coming from the scalar partner of the Goldstino (sgoldstino), restoring perturbative unitarity up to the Planck scale. This is expected since supersymmetry is spontaneously broken, in analogy with the situation occuring in the Standard Model, where massive gauge bosons scattering preserves unitarity at high energy once we consider the contributions from the Higgs boson. However, when supersymmetry is broken by the new Fayet-Iliopoulos D-term, with ungauged R-symmetry, the above cancellation does not occur. In this case, the unbroken phase is singular and there is no contribution able to cancel the quartic divergences of the amplitudes, leading to a cutoff Λ ~ MSUSY where the effective theory breaks down. The same behaviour is obtained when supersymmetry is non-linearly realised.
A plethora of Type IIA embeddings for d = 5 minimal supergravity
Authors: Couzens Christopher , Macpherson Niall T. , Passias Achilleas 
Published: January 2023

Abstract
We construct multiple embeddings of all solutions of d = 5 minimal (un)gauged supergravity into massive Type IIA supergravity. The internal spaces and warpings of such embeddings are the same as those of the $$ \mathcal{N} $$
N
= 1 supersymmetric (Mink5) AdS5 vacua, with the slight modification that the U(1) R-symmetry direction becomes fibered over the external space by the d = 5 gauge field. In addition the fluxes are appropriately modified. There are many distinct types of the aforementioned internal spaces and as such many different embeddings of the d = 5 supergravity. As examples of our setup we provide new solutions dual to six-dimensional, $$ \mathcal{N} $$
N
= (1, 0) SCFTs compactified on the product of a constant curvature Riemann surface and a spindle. We also provide a multitude of massive Type IIA embeddings for rotating, asymptotically AdS5 black hole solutions.
Loss of RREB1 in pancreatic beta cells reduces cellular insulin content and affects endocrine cell gene expression
Authors: Mattis Katia K. , Krentz Nicole A. J. , Metzendorf Christoph , Abaitua Fernando , Spigelman Aliya F. , Sun Han , Ikle Jennifer M. , Thaman Swaraj , Rottner Antje K. , Bautista Austin , Mazzaferro Eugenia , Perez-Alcantara Marta , Manning Fox Jocelyn E. , Torres Jason M. , Wesolowska-Andersen Agata , Yu Grace Z. , Mahajan Anubha , Larsson Anders , MacDonald Patrick E. , Davies Benjamin , den Hoed Marcel , Gloyn Anna L. 
Published: January 2023

Abstract
Aims/hypothesis
Genome-wide studies have uncovered multiple independent signals at the RREB1 locus associated with altered type 2 diabetes risk and related glycaemic traits. However, little is known about the function of the zinc finger transcription factor Ras-responsive element binding protein 1 (RREB1) in glucose homeostasis or how changes in its expression and/or function influence diabetes risk.

Methods
A zebrafish model lacking rreb1a and rreb1b was used to study the effect of RREB1 loss in vivo. Using transcriptomic and cellular phenotyping of a human beta cell model (EndoC-βH1) and human induced pluripotent stem cell (hiPSC)-derived beta-like cells, we investigated how loss of RREB1 expression and activity affects pancreatic endocrine cell development and function. Ex vivo measurements of human islet function were performed in donor islets from carriers of RREB1 type 2 diabetes risk alleles.

Results
CRISPR/Cas9-mediated loss of rreb1a and rreb1b function in zebrafish supports an in vivo role for the transcription factor in beta cell mass, beta cell insulin expression and glucose levels. Loss of RREB1 also reduced insulin gene expression and cellular insulin content in EndoC-βH1 cells and impaired insulin secretion under prolonged stimulation. Transcriptomic analysis of RREB1 knockdown and knockout EndoC-βH1 cells supports RREB1 as a novel regulator of genes involved in insulin secretion. In vitro differentiation of RREB1KO/KO hiPSCs revealed dysregulation of pro-endocrine cell genes, including RFX family members, suggesting that RREB1 also regulates genes involved in endocrine cell development. Human donor islets from carriers of type 2 diabetes risk alleles in RREB1 have altered glucose-stimulated insulin secretion ex vivo, consistent with a role for RREB1 in regulating islet cell function.

Conclusions/interpretation
Together, our results indicate that RREB1 regulates beta cell function by transcriptionally regulating the expression of genes involved in beta cell development and function.

Graphical abstract
Immersive movies: the effect of point of view on narrative engagement
Authors: Cannavò Alberto , Castiello Antonio , Pratticò F. Gabriele , Mazali Tatiana , Lamberti Fabrizio 
Published: January 2023

AbstractCinematic virtual reality (CVR) offers filmmakers a wide range of possibilities to explore new techniques regarding movie scripting, shooting and editing. Despite the many experiments performed so far both with both live action and computer-generated movies, just a few studies focused on analyzing how the various techniques actually affect the viewers’ experience. Like in traditional cinema, a key step for CVR screenwriters and directors is to choose from which perspective the viewers will see the scene, the so-called point of view (POV). The aim of this paper is to understand to what extent watching an immersive movie from a specific POV could impact the narrative engagement (NE), i.e., the viewers’ sensation of being immersed in the movie environment and being connected with its characters and story. Two POVs that are typically used in CVR, i.e., first-person perspective (1-PP) and external perspective (EP), are investigated through a user study in which both objective and subjective metrics were collected. The user study was carried out by leveraging two live action 360° short films with distinct scripts. The results suggest that the 1-PP experience could be more pleasant than the EP one in terms of overall NE and narrative presence, or even for all the NE dimensions if the potential of that POV is specifically exploited.
Extending the breadth of saliva metabolome fingerprinting by smart template strategies and effective pattern realignment on comprehensive two-dimensional gas chromatographic data
Authors: Squara Simone , Manig Friederike , Henle Thomas , Hellwig Michael , Caratti Andrea , Bicchi Carlo , Reichenbach Stephen E. , Tao Qingping , Collino Massimo , Cordero Chiara 
Published: January 2023

AbstractComprehensive two-dimensional gas chromatography with time-of-flight mass spectrometry (GC × GC-TOFMS) is one the most powerful analytical platforms for chemical investigations of complex biological samples. It produces large datasets that are rich in information, but highly complex, and its consistency may be affected by random systemic fluctuations and/or changes in the experimental parameters. This study details the optimization of a data processing strategy that compensates for severe 2D pattern misalignments and detector response fluctuations for saliva samples analyzed across 2 years. The strategy was trained on two batches: one with samples from healthy subjects who had undergone dietary intervention with high/low-Maillard reaction products (dataset A), and the second from healthy/unhealthy obese individuals (dataset B). The combined untargeted and targeted pattern recognition algorithm (i.e., UT fingerprinting) was tuned for key process parameters, the signal-to-noise ratio (S/N), and MS spectrum similarity thresholds, and then tested for the best transform function (global or local, affine or low-degree polynomial) for pattern realignment in the temporal domain. Reliable peak detection achieved its best performance, computed as % of false negative/positive matches, with a S/N threshold of 50 and spectral similarity direct match factor (DMF) of 700. Cross-alignment of bi-dimensional (2D) peaks in the temporal domain was fully effective with a supervised operation including multiple centroids (reference peaks) and a match-and-transform strategy using affine functions. Regarding the performance-derived response fluctuations, the most promising strategy for cross-comparative analysis and data fusion included the mass spectral total useful signal (MSTUS) approach followed by Z-score normalization on the resulting matrix.
A Bayesian hierarchical spatio-temporal model for extreme temperatures in Extremadura (Spain) simulated by a Regional Climate Model
Authors: García José Agustín , Acero Francisco Javier , Portero Javier 
Published: January 2023

AbstractA statistical study was made of the temporal trend in extreme temperatures in the region of Extremadura (Spain) during the period 1981–2015 using a Regional Climate Model. For this purpose, a Weather Research and Forecasting (WRF) Regional Climate Model extreme temperature dataset was obtained. This dataset was then subjected to a statistical study using a Bayesian hierarchical spatio-temporal model with a Generalized Extreme Value (GEV) parametrization of the extreme data. The Bayesian model was implemented in a Markov chain Monte Carlo framework that allows the posterior distribution of the parameters that intervene in the model to be estimated. The role of the altitude dependence of the temperature was considered in the proposed model. The results for the spatial-trend parameter lend confidence to the model since they are consistent with the dry adiabatic gradient. Furthermore, the statistical model showed a slight negative trend for the location parameter. This unexpected result may be due to the internal and modeling uncertainties in the WRF model. The shape parameter was negative, meaning that there is an upper bound for extreme temperatures in the model.
Sub-exponential Time Parameterized Algorithms for Graph Layout Problems on Digraphs with Bounded Independence Number
Authors: Misra Pranabendu , Saurabh Saket , Sharma Roohani , Zehavi Meirav 
Published: January 2023

AbstractFradkin and Seymour (J Comb Theory Ser B 110:19–46, 2015) defined the class of digraphs of bounded independence number as a generalization of the class of tournaments. They argued that the class of digraphs of bounded independence number is structured enough to be exploited algorithmically. In this paper, we further strengthen this belief by showing that several cut problems that admit sub-exponential time parameterized algorithms (a trait uncommon to parameterized algorithms) on tournaments, including Directed Feedback Arc Set, Directed Cutwidth and Optimal Linear Arrangement, also admit such algorithms on digraphs of bounded independence number. Towards this, we rely on the generic approach of Fomin and Pilipczuk (in: Proceedings of the Algorithms—ESA 2013—21st Annual European Symposium, Sophia Antipolis, France, September 2–4, 2013, pp. 505–516, 2013), where to get the desired algorithms, it is enough to bound the number of k-cuts in digraphs of bounded independence number by a sub-exponential FPT function (Fomin and Pilipczuk bounded the number of k-cuts in transitive tournaments). Specifically, our main technical contribution is a combinatorial result that proves that the yes-instances of the problems (defined above) have a sub-exponential number of k-cuts. We prove this bound by using a combination of chromatic coding, inductive reasoning and exploiting the structural properties of these digraphs.
Accelerating inexact successive quadratic approximation for regularized optimization through manifold identification
Authors: Lee Ching-pei 
Published: January 2023

AbstractFor regularized optimization that minimizes the sum of a smooth term and a regularizer that promotes structured solutions, inexact proximal-Newton-type methods, or successive quadratic approximation (SQA) methods, are widely used for their superlinear convergence in terms of iterations. However, unlike the counter parts in smooth optimization, they suffer from lengthy running time in solving regularized subproblems because even approximate solutions cannot be computed easily, so their empirical time cost is not as impressive. In this work, we first show that for partly smooth regularizers, although general inexact solutions cannot identify the active manifold that makes the objective function smooth, approximate solutions generated by commonly-used subproblem solvers will identify this manifold, even with arbitrarily low solution precision. We then utilize this property to propose an improved SQA method,$$^{+}$$+, that switches to efficient smooth optimization methods after this manifold is identified. We show that for a wide class of degenerate solutions,$$^{+}$$+possesses superlinear convergence not only in iterations, but also in running time because the cost per iteration is bounded. In particular, our superlinear convergence result holds on problems satisfying a sharpness condition that is more general than that in existing literature. We also prove iterate convergence under a sharpness condition for inexact SQA, which is novel for this family of methods that could easily violate the classical relative-error condition frequently used in proving convergence under similar conditions. Experiments on real-world problems support that$$^{+}$$+improves running time over some modern solvers for regularized optimization.
Reference Correlation for the Viscosity of Ethanol from the Triple Point to 620 K and Pressures Up to 102 MPa
Authors: Sotiriadou Sofia , Ntonti Eleftheria , Velliadou Danai , Antoniadis Konstantinos D. , Assael Marc J. , Huber Marcia L. 
Published: January 2023

AbstractWe present a wide-ranging correlation expressed in terms of temperature and density for the viscosity of ethanol based on critically evaluated experimental data. The correlation is designed to be used with an existing equation of state from the triple point (159 K) to 620 K and at pressures up to 102 MPa. Comparisons with experimental data indicate the estimated uncertainty of the correlation is 4.2 % (at the 95 % confidence level) for the liquid and supercritical phase at pressures up to 102 MPa, and 2 % in the gas phase. Furthermore, for calculating viscosity values at 0.1 MPa, an additional correlation is proposed, valid from the triple point to the boiling point with an estimated uncertainty of 2.3 % (at the 95 % confidence level).
Multivariate Cross-Validation and Measures of Accuracy and Precision
Authors: Mueller Ute , Selia Sangga Rima Roman , Tolosana-Delgado Raimon 
Published: January 2023

AbstractCross-validation and performance measures are standard components in the evaluation of a geostatistical model. These are well established in the univariate case, but measures for multivariate geostatistical modeling have not received as much attention. In the case of a single target variable, the univariate approaches remain valid, but in the fully multivariate case where a vector of variables needs to be estimated, the evaluation needs to be based on all estimates simultaneously. An extension of cross-validation and associated performance measures to the fully multivariate case is presented and discussed for the case of regionalized compositions. The method is demonstrated by validating geostatistical models for two case studies: a sample drawn from a geochemical survey data set estimated with cokriging, and an application of direct sampling multiple-point simulation.