bluuebunny/crossref_metadata_2025 huggingface dataset:
Pediatric severe factor XI deficiency: A multicenter study
Authors: Barg Assaf Arie , Levy‐Mendelovich Sarina , Budnik Ivan , Mandel‐Shorer Noa , Dardik Rima , Avishai Einat , Brutman‐Barazani Tami , Ifrah Aviya Dvir , Oren‐Malek Liat , Yacobovich Joanne , Gilad Oded , Nakav Sigal , Fruchtman Yariv , Revel‐Vilk Shoshana , Miskin Hagit , Kenet Gili
Published: December 2021

Background

Factor XI (FXI) deficiency is a rare autosomal recessive bleeding disorder. Only scarce publications address its clinical features in children. The increased prevalence of FXI deficiency in Israel enabled data collection for this large multicenter cohort study.

Objective

Some hemostatic challenges may be unique or more common in children, such as bleeding in the neonatal period or trauma‐related injury. The current study was designed to explore the potential impact of these differences in children with severe FXI deficiency.

Methods

Medical files of all children with FXI level under 15% followed at five tertiary centers were evaluated. The retrieved data comprised demographic and clinical characteristics, including bleeding episodes, surgical interventions, treatment strategies, as well as laboratory features.

Results

Sixty children, whose median age at diagnosis was 4.2 years and their median FXI level was 4%, were included. Three children experienced triggered intracranial hemorrhage (ICH) and two children had major bleeds. No bleeding complications occurred in surgeries in which hemostatic treatment consisting mostly of tranexamic acid or fresh frozen plasma was applied (n = 45). In contrast, excessive bleeding was noted in 25% of surgical procedures performed without hemostatic preparation (p = .002).

Conclusion

This study's findings confirm the generally favorable outcome of this rare bleeding disorder, with no spontaneous bleeds or cases of perinatal ICH. Nonetheless, proper diagnosis and adequate hemostasis in the surgical setting are imperative. Unlike previous studies in adults, our pediatric study suggests an association between the severity of FXI deficiency and bleeding tendency.
Trio exome sequencing is highly relevant in prenatal diagnostics
Authors: Gabriel Heinz , Korinth Dirk , Ritthaler Martin , Schulte Björn , Battke Florian , von Kaisenberg Constantin , Wüstemann Max , Schulze Bernt , Friedrich‐Freksa Almuth , Pfeiffer Lutz , Entezami Michael , Schröer Andreas , Bürger Joachim , Schwaibold Eva Maria Christina , Lebek Holger , Biskup Saskia
Published: December 2021

Objective

About 3% of newborns show malformations, with about 20% of the affected having genetic causes. Clarification of genetic diseases in postnatal diagnostics was significantly improved with high‐throughput sequencing, in particular through whole exome sequencing covering all protein‐coding regions. Here, we aim to extend the use of this technology to prenatal diagnostics.

Method

Between 07/2018 and 10/2020, 500 pregnancies with fetal ultrasound abnormalities were analyzed after genetic counseling as part of prenatal diagnostics using WES of the fetus and parents.

Results

Molecular genetic findings could explain ultrasound abnormalities in 38% of affected fetuses. In 47% of these, disease‐causing de novo variants were found. Pathogenic variants in genes with autosomal recessive or X‐linked inheritance were detected in more than one‐third (70/189 = 37%). The latter are associated with increased probability of recurrence, making their detection important for further pregnancies. Average time from sample receipt to report was 12 days in the recent cases.

Conclusion

Trio exome sequencing is a useful addition to prenatal diagnostics due to its high diagnostic yield and short processing time (comparable to chromosome analysis). It covers a wide spectrum of genetic changes. Comprehensive interdisciplinary counseling before and after diagnostics is indispensable.
Distinct C4 sub‐types and C3 bundle sheath isolation in the Paniceae grasses
Authors: Washburn Jacob D. , Strable Josh , Dickinson Patrick , Kothapalli Satya S. , Brose Julia M. , Covshoff Sarah , Conant Gavin C. , Hibberd Julian M. , Pires Joseph Chris
Published: December 2021

In C4 plants, the enzymatic machinery underpinning photosynthesis can vary, with, for example, three distinct C4 acid decarboxylases being used to release CO2 in the vicinity of RuBisCO. For decades, these decarboxylases have been used to classify C4 species into three biochemical sub‐types. However, more recently, the notion that C4 species mix and match C4 acid decarboxylases has increased in popularity, and as a consequence, the validity of specific biochemical sub‐types has been questioned. Using five species from the grass tribe Paniceae, we show that, although in some species transcripts and enzymes involved in multiple C4 acid decarboxylases accumulate, in others, transcript abundance and enzyme activity is almost entirely from one decarboxylase. In addition, the development of a bundle sheath isolation procedure for a close C3 species in the Paniceae enables the preliminary exploration of C4 sub‐type evolution.
Exploring the reaction pathway involved in the dibenzo‐18‐crown‐6 synthesis from catechol and bis(2‐chloroethyl) ether in presence of base
Authors: Sisodiya Dilawar Singh , Ali Sk. Musharaf , Chattopadhyay Anjan
Published: December 2021

Computational investigations reported in this work have proposed the mechanism involved in the synthesis of dibenzo‐18‐crown‐6 (DB18C6) from catechol and bis(2‐chloroethyl) ether in presence of base. The transition states on the reaction path have been identified, and the corresponding barrier heights are estimated. Paths related to the side‐product formations, such as benzo‐9‐crown‐3 and 1,2‐bis[2‐(2‐chloroethoxy)ethoxy]‐benzene, have been also tracked. The cation‐assisted (Na+ and K+ ions) cyclization process (template effect) creates more structurally ordered reactant and transition state species. This facilitates the cyclization step that is an intramolecular SN2 process. Additionally, it eliminates possibilities of different side‐product formations giving better yield of the crown ether, as reported previously. This cyclization step has a comparatively lower barrier height for Na+ system (by 3 kcal/mol) in gas phase than K+ system; however, it becomes reverse in 1‐butanol where the barrier height is almost 2.5 kcal/mol lower during the K+DB18C6 formation. Consequently, a faster cyclization has been found in this solvent from the reaction rate studies for the potassium system. This is in‐line with the experimental observations reported on the alkali‐metal‐catalyzed benzo‐18‐crown‐6 ether formation reactions. The dipole moment value of the transition state involved in this step for the larger alkali metal ion system is found to be significantly higher (by 5–8 D) than the reactant species.
High Catalytic Performance of Silver‐Doped Gold Nanocages for Methanol Electrooxidation
Authors: You Hongjun , Zhao Lijun , Zuo Yun , Fang Jixiang
Published: December 2021

Hollow or porous noble metal nanocrystals with large specific electrochemical surface area and stability hold stimulating technological applications in fuel cell catalysis. Here, a simple galvanic replacement reaction synthesis of Ag‐doped Au nanocages with a tunable Ag/Au atomic ratio is developed. Without surface ligands being used in the synthesis, the obtained AuAg nanocages with hollow cavity and opened nanoporous shell possess clean surface and enhanced electrocatalytic activity. In the electrocatalysis of the methanol oxidation reaction (MOR), the obtained AuAg nanocages possess high electrocatalysis properties and show morphology and composition‐dependent electrocatalytic property. The optimized AuAg cubic nanocages that have 5% Ag exhibit excellent electrocatalytic activity for MOR, and this is attributed to the unique geometric structure and the well‐controlled Ag content. The hollow and nanoporous structure can effectively promote the mass transfer and atomic utilization during the catalytic process for MOR. Density functional theory calculations indicate that introducing of a small amount of Ag facilitates methanol adsorption to the surface of catalysts and promotes the break of the OH bond during the MOR process, thus accordingly enhances the catalytic activity.
Luminescence and Vacuum Ultraviolet Excitation Spectroscopy of Nanophosphors under Synchrotron Irradiation
Authors: Pankratov Vladimir , Pankratova Viktorija , Popov Anatoli I.
Published: December 2021

Vacuum ultraviolet (VUV) excitation spectroscopy under synchrotron irradiation is a powerful tool for the investigation of luminescence properties of wide bandgap nanocrystalline phosphor materials. The advantages of selective excitation in a wide spectral range present the possibility to explore the different aspects of luminescence processes in nanophosphors separately. It is shown that direct excitations of emission centers in wide bandgap materials need excitations in VUV spectral range and such excitations provide valuable information about f–f, f–d transitions, defects, and excitonic transitions in wide bandgap nanophosphors. It is also demonstrated that size‐dependent luminescence properties of nanophosphors are significant if the electron thermalization length becomes larger than the size of the nanoparticles. In this case, multiplication of electronic excitations processes well‐known in bulk materials are suppressed strongly in nanophosphors.
Molecular representations for machine learning applications in chemistry
Authors: Raghunathan Shampa , Priyakumar U. Deva
Published: December 2021

Machine learning (ML) methods enable computers to address problems by learning from existing data. Such applications are becoming commonplace in molecular sciences. Interest in applying ML techniques across chemical compound space, from predicting properties to designing molecules and materials is in the surge. Especially, ML models have started to accelerate computational chemistry, and are often as accurate as state‐of‐the‐art electronic/atomistic models. Being an integral part of the ML architecture, representation of a molecular entity, uniquely encoded, plays a crucial role to what extent an ML model would be accurately predicting the desired property. This review aims to demonstrate a hierarchy of representations which has been introduced, to capture all degrees of freedom of a molecule or an atom the best, to map the quantum mechanical properties. We discuss their diverse applications how they have been instrumental in harnessing the growing field of ML accelerated computational modeling.
Adapting automated instrumentation for high‐throughput calcium isotope measurements by multi‐collector inductively coupled plasma mass spectrometry
Authors: Razionale Dan , Bryant Roger N. , Blättler Clara L.
Published: December 2021

Rationale

Large, efficiently generated datasets of calcium isotope ratios offer tremendous utility in an increasing number of scientific disciplines. Modern analytical capabilities in mass spectrometry present unique challenges to previously established sample preparation techniques, the extent of which must be thoroughly examined before these data are interpreted and reported. This study addresses key methodological challenges in the determination of calcium isotopes using state‐of‐the‐art, commercially available instruments.

Methods

Automated ion chromatography was used to isolate calcium from carbonate‐ and seawater‐like samples prior to analysis by multi‐collector inductively coupled plasma mass spectrometry (MC‐ICP‐MS). A new, membrane‐bearing desolvator (Apex‐Ω) is implemented and achieves enhanced sensitivity, yet necessitates an update to established sample preparation techniques due to previously unobserved matrix effects. Performance of this method was assessed through analyses of multiple standard reference materials (SRM 915b, USGS EN‐1, and seawater) and several in‐house standards using a Neptune MC‐ICP‐MS instrument.

Results

The enhanced sensitivity afforded by the Apex‐Ω also yields pronounced matrix effects during mass spectrometry, resulting specifically from heightened sample Na and Sr content and deviations in sample [Ca] from their bracketing standards. While the latter can be addressed by a concentration correction, the first two matrix effects are mitigated using a modified chromatography technique that implements unique rinsing protocols.

Conclusions

This precise (0.14‰ 2σ), high‐throughput method is very reproducible for small sample amounts and, at optimal efficiency, can generate approximately 140 sample δ44/40Ca values per week with 5 h of in‐person effort per day. Documented matrix effects are successfully mitigated through corrections and modified chromatographic techniques. Additionally, this method may be permuted to accommodate most major cations.
Asymptotic stabilization with group‐wise sparse input based on control Lyapunov function approach
Authors: Yamashita Yuh , Sakano Kiminori , Kobayashi Koichi
Published: December 2021

This study proposes a novel stabilizing controller for nonlinear systems using group‐wise sparse inputs. The input variables are divided into several groups. In the situations when the input constraints can be ignored, one input becomes active for each group at each moment. Our method improves energy efficiency, as sparse input vectors often reduce the standby power of inactive actuators. Large‐scale systems, such as those consisting of multiple subsystems, often require the manipulation of multiple inputs simultaneously to be controlled. Our method can be applied to such systems due to the group‐wise sparsity of the inputs. The proposed controller is based on the control Lyapunov function approach and includes Sontag's universal formula as a special case. The controllers designed in our method have best‐effort property, which means even when a restriction for the decreasing rate of the Lyapunov function cannot be fulfilled, the controller minimizes the time derivative of the Lyapunov function within the input constraint. The effectiveness of the proposed method can be confirmed through simulations.
The effects of soil solarization and application of a Trichoderma biocontrol agent on soil fungal and prokaryotic communities
Authors: Funahashi Fumiaki , Myrold David D. , Parke Jennifer L.
Published: December 2021

Soil solarization and biological control are two management strategies that have been used globally to manage soil‐borne plant pathogens. However, the broader effects of these strategies on soil microbial communities have not been well described. Soil prokaryotic and fungal communities were investigated by environmental DNA amplicon sequencing as part of field trials conducted in San Rafael, CA, and in Corvallis, OR. We examined microbial community changes following soil solarization, amendment with the biocontrol agent Trichoderma asperellum (TA), or solarization followed by application of the biocontrol agent. Soil solarization caused significant changes to prokaryotic and fungal communities by reducing species richness and diversity. Soil water potential was determined to be a significant factor affecting the prokaryotic community. Application of TA to solarized or nonsolarized soil did not significantly alter the microbial communities. However, solarization resulted in diminished microbial densities that appeared to enhance subsequent establishment of the biocontrol agent. This study revealed how specific environmental variables of heat intensity and soil moisture contribute to changes in the abundance of individual taxa and taxonomic groups.
In Situ Liquid Electrochemical TEM Investigation of LiMn1.5Ni0.5O4 Thin Film Cathode for Micro‐Battery Applications
Authors: Bhatia Ankush , Cretu Sorina , Hallot Maxime , Folastre Nicolas , Berthe Maxime , Troadec David , Roussel Pascal , Pereira‐Ramos Jean‐Pierre , Baddour‐Hadjean Rita , Lethien Christophe , Demortière Arnaud
Published: December 2021

Micro‐batteries are attractive miniaturized energy devices for new Internet of Things applications, but the lack of understanding of their degradation process during cycling hinders improving their performance. Here focused ion beam (FIB)‐lamella from LiMn1.5Ni0.5O4 (LMNO) thin‐film cathode is in situ cycled in a liquid electrolyte inside an electrochemical transmission electron microscope (TEM) holder to analyze structural and morphology changes upon (de)lithiation processes. A high‐quality electrical connection between the platinum (Pt) current collector of FIB‐lamella and the microchip's Pt working electrode is established, as confirmed by local two‐probe conductivity measurements. In situ cyclic voltammetry (CV) experiments show two redox activities at 4.41 and 4.58/4.54 V corresponding to the Ni2+/3+ and Ni3+/4+ couples, respectively. (S)TEM investigations of the cycled thin‐film reveal formation of voids and cracks, loss of contact with current collector, and presence of organic decomposition products. The 4D STEM ASTAR technique highlights the emergence of an amorphization process and a decrease in average grain size from 20 to 10 nm in the in situ cycled electrode. The present findings, obtained for the first time through the liquid electrochemical TEM study, provide several insights explaining the capacity fade of the LMNO thin‐film cathode typically observed upon cycling in a conventional liquid electrolyte.
Bioinspired Materials for Energy Storage
Authors: Mei Jun , Liao Ting , Peng Hong , Sun Ziqi
Published: December 2021

Nature offers a variety of interesting structures and intriguing functions for researchers to be learnt for advanced materials innovations. Recently, bioinspired materials have received intensive attention in energy storage applications. Inspired by various natural species, many new configurations and components of energy storage devices, such as rechargeable batteries and supercapacitors, have been designed and innovated. The bioinspired designs on energy devices, such as electrodes and electrolytes, have brought about excellent physical, chemical, and mechanical properties compared to the counterparts at their conventional forms. In this review, the design principles for bioinspired materials ranging from structures, synthesis, and functionalization to multi‐scale ordering and device integration are first discussed, and then a brief summary is given on the recent progress on bioinspired materials for energy storage systems, particularly the widely studied rechargeable batteries and supercapacitors. Finally, a critical review on the current challenges and brief perspective on the future research focuses are proposed. It is expected that this review can offer some insights into the smart energy storage system design by learning from nature.
Label‐Free and In Situ Identification of Cells via Combinational Machine Learning Models
Authors: Xue Yun‐fan , He Yang , Wang Jing , Ren Ke‐feng , Tian Pu , Ji Jian
Published: December 2021

Cell identification and counting in living and coculture systems are crucial in cell interaction studies, but current methods primarily rely on complicated and time‐consuming staining techniques. Here, a label‐free method to precisely recognize, identify, and instantly count cells in situ in coculture systems via combinational machine learning models s presented. A convolutional neural network (CNN) model is first used to generate virtual images of cell nuclei based on unlabeled phase‐contrast images. Coordinates of all the cells are then returned according to the virtual nucleus images using two clustering algorithms. Finally, phase‐contrast images of single cells are cropped based on the coordinates and sent into another CNN model for cell‐type identification. This combinational approach is highly automatic and efficient, which requires few to no manual annotations of images in the training phase. It shows practical performance in different cell culture conditions including cell ratios, densities, and substrate materials, having great potential in real‐time cell tracking and analyzing.
Economic supply chain management of advanced manufacturing industry based on blockchain technology
Authors: Zhang Erni
Published: December 2021

Advanced manufacturing industry is the core of modern manufacturing industry, which is related to the overall situation of the whole national economic and social development. This study mainly discusses the advanced manufacturing economic supply chain management under the blockchain (BC) technology. The smart contract function in the BC will strengthen the execution of credit agreements between enterprises. In the application scenario of smart contract, as long as one party performs its economic activities, the system will force the other party to perform the contract directly, which improves the credibility of all parties in the chain and reduces the risk of default. To avoid false trade, commercial factoring risk management, one is to establish a cooperative relationship with banks. The second is to issue asset securitization products. Third, cooperate with internet financial platform. In 2018, under the background of slower growth in operating income, the balance of accounts receivable of enterprises fell more, and 2019 performance it began to pick up, and the substantial increase in operating income has also brought about a substantial increase in accounts receivable. Since then, operating income has maintained a rapid growth rate, but the balance of accounts receivable has not increased significantly, but has decreased slightly. After the implementation of supply chain financing, the proportion of accounts receivable of B advanced manufacturing company in operating revenue has decreased from 23.17% in 2018 to 13.45% in 2020. The implementation of supply chain financing designed in this study helps advanced manufacturing companies to control the balance of accounts receivable.
Role of Stat3 in NLRP3/caspase‐1‐mediated hippocampal neuronal pyroptosis in epileptic mice
Authors: Jiang Qian , Tang Guo , Zhong Xue‐Min , Ding Dan‐Rui , Wang Hui , Li Jia‐Ni
Published: December 2021

Epilepsy, a fairly common neurological disorder, is linked to various sequelae and greatly impairs the quality of life. Meanwhile, there is evidence to suggest an association between pyroptosis and epilepsy. Accordingly, the current study sought to determine the role of signal transduction activator of transcription 3 (Stat3) in pyroptosis in epileptic mice. First, epileptic mouse models were induced by lithium chloride, atropine, and pilocarpine, and HT22 cells were treated with lipopolysaccharide (LPS) to establish in vitro hippocampal neuronal inflammation models. Subsequently, Stat3, NOD‐like receptor protein 3 (NLRP3), cleaved‐caspase‐1, gasdermin D (GSDMD)‐N, activated Stat3 (p‐Stat3), and H3K9Ac levels were detected in the mouse hippocampus and HT22 cells. Morris water maze test was further performed to detect changes in the learning and memory abilities of epileptic mice, and hematoxylin‐eosin staining and Nissl staining were conducted to detect the pathological injury. HT22 cell proliferation and apoptosis were also detected using a cell counting kit‐8 assay and flow cytometry. An enzyme‐linked immunosorbent assay was adopted to detect Interleukin (IL)‐1β and IL‐18 concentrations in the mouse hippocampus and HT22 cells. Furthermore, the enrichment of H3K9Ac and p‐Stat3 in the NLRP3 promoter region was detected with the help of a chromatin immunoprecipitation assay. The obtained findings revealed that Stat3 was highly expressed in the hippocampus of epileptic mice and LPS‐treated HT22 cells. Meanwhile, Stat3 silencing brought about improvements in the learning and memory abilities of the mice, in addition to alleviation of hippocampal neuronal damage and pyroptosis‐related factors in hippocampal tissue and HT22 cells. We also observed that Stat3 bound to the NLRP3 promoter to promote H3K9 acetylation and NLRP3 transcription. Moreover, increasing H3K9Ac in cells annulled the inhibition of silencing Stat3 on neuronal pyroptosis. To conclude, our findings revealed that Stat3 bound to the NLRP3 promoter to augment H3K9 acetylation, NLRP3 transcription, and NLRP3/caspase‐1‐mediated neuronal pyroptosis, resulting in aggravation of neuronal damage in epileptic mice.
Anaesthetic management and complications during cutting balloon and high‐pressure balloon dilation in a dog with a double‐chambered right ventricle
Authors: Sambugaro Beatrice , De Gennaro Chiara , Vettorato Enzo
Published: December 2021

A 3‐month‐old female Cocker Spaniel was presented for investigation of a V/VI left basilar heart murmur and diagnosed with a double‐chambered right ventricle. Atenolol was prescribed for 3 months before surgical correction of the congenital anomaly, combining cutting balloon and high‐pressure balloon (CB‐HPB) dilation. A few days before the intervention, the dog showed signs of right‐sided congestive heart failure and it was treated with furosemide, benazepril/spironolactone and pleural effusion were drained. During CB‐HPB dilation, cardiac index and systemic arterial blood pressure suddenly decreased on two occasions probably secondary to a dynamic right ventricular outflow tract obstruction. Cardiac arrest occurred and cardiopulmonary resuscitation was unsuccessful.
Off-shell higher-spin fields in AdS4 and external currents
Authors: Misuna N.G.
Published: December 2021

Abstract

We construct an unfolded system for off-shell fields of arbitrary integer spin in 4d anti-de Sitter space. To this end we couple an on-shell system, encoding Fronsdal equations, to external Fronsdal currents for which we find an unfolded formulation. We present a reduction of the Fronsdal current system which brings it to the unfolded Fierz-Pauli system describing massive fields of arbitrary integer spin. Reformulating off-shell higher-spin system as the set of Schwinger–Dyson equations we compute propagators of higher-spin fields in the de Donder gauge directly from the unfolded equations. We discover operators that significantly simplify this computation, allowing a straightforward extraction of wave equations from an unfolded system.
Mirror channel eigenvectors of the d-dimensional fishnets
Authors: Derkachov Sergey , Ferrando Gwenaël , Olivucci Enrico
Published: December 2021

Abstract

We present a basis of eigenvectors for the graph building operators acting along the mirror channel of planar fishnet Feynman integrals in d-dimensions. The eigenvectors of a fishnet lattice of length N depend on a set of N quantum numbers (uk, lk ), each associated with the rapidity and bound-state index of a lattice excitation. Each excitation is a particle in (1 + 1)-dimensions with O(d) internal symmetry, and the wave-functions are formally constructed with a set of creation/annihilation operators that satisfy the corresponding Zamolodchikovs-Faddeev algebra. These properties are proved via the representation, new to our knowledge, of the matrix elements of the fused R-matrix with O(d) symmetry as integral operators on the functions of two spacetime points. The spectral decomposition of a fishnet integral we achieved can be applied to the computation of Basso-Dixon integrals in higher dimensions.
Warm inflation, neutrinos and dark matter: a minimal extension of the Standard Model
Authors: Levy Miguel , Rosa João G. , Ventura Luís B.
Published: December 2021

Abstract

We show that warm inflation can be realized within a minimal extension of the Standard Model with three right-handed neutrinos, three complex scalars and a gauged lepton/B-L U(1) symmetry. This simple model can address all the shortcomings of the Standard Model that are not related to fine-tuning, within general relativity, with distinctive experimental signatures that can be probed in the near future. The inflaton field emerges from the collective breaking of the U(1) symmetry, and interacts with two of the right-handed neutrinos, sustaining a high-temperature radiation bath during inflation. The discrete interchange symmetry of the model protects the scalar potential against large thermal corrections and leads to a stable inflaton remnant at late times which can account for dark matter. Consistency of the model and agreement with Cosmic Microwave Background observations naturally yield light neutrino masses below 0.1 eV, while thermal leptogenesis occurs naturally after a smooth exit from inflation into the radiation era.
Do lower nitrogen fertilization levels require breeding of different types of cultivars in triticale?
Authors: Neuweiler Jan E. , Trini Johannes , Maurer Hans Peter , Würschum Tobias
Published: December 2021

Key message

The comparably low genotype-by-nitrogen level interaction suggests that selection in early generations can be done under high-input conditions followed by selection under different nitrogen levels to identify genotypes ideally suited for the target environment.

Breeding high-yielding, nitrogen-efficient crops is of utmost importance to achieve greater agricultural sustainability. The aim of this study was to evaluate nitrogen use efficiency (NUE) of triticale, investigate long-term genetic trends and the genetic architecture, and develop strategies for NUE improvement by breeding. For this, we evaluated 450 different triticale genotypes under four nitrogen fertilization levels in multi-environment field trials for grain yield, protein content, starch content and derived indices. Analysis of temporal trends revealed that modern cultivars are better in exploiting the available nitrogen. Genome-wide association mapping revealed a complex genetic architecture with many small-effect QTL and a high level of pleiotropy for NUE-related traits, in line with phenotypic correlations. Furthermore, the effect of some QTL was dependent on the nitrogen fertilization level. High correlations of each trait between N levels and the rather low genotype-by-N-level interaction variance showed that generally the same genotypes perform well over different N levels. Nevertheless, the best performing genotype was always a different one. Thus, selection in early generations can be done under high nitrogen fertilizer conditions as these provide a stronger differentiation, but the final selection in later generations should be conducted with a nitrogen fertilization as in the target environment.
Studying human-to-computer bias transference
Authors: Johansen Johanna , Pedersen Tore , Johansen Christian
Published: December 2021

It is generally agreed that one origin of machine bias is resulting from characteristics within the dataset on which the algorithms are trained, i.e., the data does not warrant a generalized inference. We, however, hypothesize that a different ‘mechanism’ may also be responsible for machine bias, namely that biases may originate from (i) the programmers’ cultural background, including education or line of work, or (ii) the contextual programming environment, including software requirements or developer tools. Combining an experimental and comparative design, we study the effects of cultural and contextual metaphors, and test whether each of these are ‘transferred’ from the programmer to the program, thus constituting a machine bias. Our results show that (i) cultural metaphors influence the programmer’s choices and (ii) contextual metaphors induced through priming can be used to moderate or exacerbate the effects of the cultural metaphors. Our studies are purposely performed with users of varying educational backgrounds and programming skills stretching from novice to proficient.
Load step reduction for adjoint sensitivity analysis of finite strain elastoplasticity
Authors: Wang Wenjia , Clausen Peter M. , Bletzinger Kai-Uwe
Published: December 2021

In this paper, load step reduction techniques are investigated for adjoint sensitivity analysis of path-dependent nonlinear finite element systems. In particular, the focus is on finite strain elastoplasticity with typical hardening models. The aim is to reduce the computational cost in the adjoint sensitivity implementation. The adjoint sensitivity formulation is derived with the multiplicative decomposition of deformation gradient, which is applicable to finite strain elastoplasticity. Two properties of adjoint variables are investigated and theoretically proved under certain prerequisites. Based on these properties, load step reduction rules in the sensitivity analysis are discussed. The efficiency of the load step reduction and the applicability to isotropic hardening and kinematic hardening models are numerically demonstrated. Examples include a small-scale cantilever beam structure and a large-scale conrod structure under huge plastic deformations.
Topology optimization of periodically arranged components using shared design domains
Authors: Rieser Jasper , Zimmermann Markus
Published: December 2021

Building structures from identical components organized in a periodic pattern is a common design strategy to reduce design effort, structural complexity and cost. However, any periodic pattern will impose certain design restrictions often leading to lower structural efficiency and heavier weight. Much research is available for periodic structures with connected components. This paper addresses minimal compliance design for periodic arrangements of unconnected components. The design problem discussed here is relevant for many applications where a tightly nested, space-saving arrangement of identical components is required. We formulate an optimal design problem for a component being part of a periodic arrangement. The orientation and position of the component relatively to its neighbours are prescribed. The component design is computed by topology optimization on a design domain possibly shared by several neighbouring components. Additional constraints prevent components from overlapping. Constraint aggregation is employed to reduce the computational cost of many local constraints. The effectiveness of the method is demonstrated by a series of 2D and 3D examples with an ever-smaller distance between the components. Moreover, problem-specific ranges with only little to no increase in compliance are reported.
Translational imaging of the fibroblast activation protein (FAP) using the new ligand [68Ga]Ga-OncoFAP-DOTAGA
Authors: Backhaus P. , Gierse F. , Burg M. C. , Büther F. , Asmus I. , Dorten P. , Cufe J. , Roll W. , Neri D. , Cazzamalli S. , Millul J. , Mock J. , Galbiati A. , Zana A. , Schäfers K. P. , Hermann S. , Weckesser M. , Tio J. , Wagner S. , Breyholz H.-J. , Schäfers M.
Published: December 2021

Purpose

The fibroblast activation protein (FAP) is an emerging target for molecular imaging and therapy in cancer. OncoFAP is a novel small organic ligand for FAP with very high affinity. In this translational study, we establish [68Ga]Ga-OncoFAP-DOTAGA (68Ga-OncoFAP) radiolabeling, benchmark its properties in preclinical imaging, and evaluate its application in clinical PET scanning.

Methods

68Ga-OncoFAP was synthesized in a cassette-based fully automated labeling module. Lipophilicity, affinity, and serum stability of 68Ga-OncoFAP were assessed by determining logD7.4, IC50 values, and radiochemical purity. 68Ga-OncoFAP tumor uptake and imaging properties were assessed in preclinical dynamic PET/MRI in murine subcutaneous tumor models. Finally, biodistribution and uptake in a variety of tumor types were analyzed in 12 patients based on individual clinical indications that received 163 ± 50 MBq 68Ga-OncoFAP combined with PET/CT and PET/MRI.

Results

68Ga-OncoFAP radiosynthesis was accomplished with high radiochemical yields. Affinity for FAP, lipophilicity, and stability of 68Ga-OncoFAP measured are ideally suited for PET imaging. PET and gamma counting–based biodistribution demonstrated beneficial tracer kinetics and high uptake in murine FAP-expressing tumor models with high tumor-to-blood ratios of 8.6 ± 5.1 at 1 h and 38.1 ± 33.1 at 3 h p.i. Clinical 68Ga-OncoFAP-PET/CT and PET/MRI demonstrated favorable biodistribution and kinetics with high and reliable uptake in primary cancers (SUVmax 12.3 ± 2.3), lymph nodes (SUVmax 9.7 ± 8.3), and distant metastases (SUVmax up to 20.0).

Conclusion

Favorable radiochemical properties, rapid clearance from organs and soft tissues, and intense tumor uptake validate 68Ga-OncoFAP as a powerful alternative to currently available FAP tracers.
The Simultaneous Presence of Isolated Tumour Cells and Bone Marrow Micrometastases in Stage I and II Colon Cancer—Challenging the Theory of a Chronological Pathway of Tumour Cell Dissemination
Authors: Ramser Michaela , Warschkow Rene , Viehl Carsten T. , Kettelhack Christoph , Zettl Andreas , Lobbes Leonard A. , Zuber Markus , Weixler Benjamin
Published: December 2021

Background

According to the common tenet, tumour progression is a chronological process starting with lymphatic invasion. In this respect, the meaning of bone marrow micrometastases (BMM) in patients with lymph node negative colon cancer (CC) is unclear. This study examines the relationship of isolated tumour cells (ITC) in sentinel lymph nodes (SLN) and BMM in patients in early CC.

Methods

BM aspirates were taken from both pelvic crests and in vivo SLN mapping was done during open oncologic colon resection in patients with stage I and II CC. Stainings were performed with the pancytokeratin markers A45‐B/B3 and AE1/AE3 as well as H&E. The correlation between the occurrence of ITC+ and BMM+ and their effects on survival was examined using Cox regression analysis.

Results

In a total of 78 patients with stage I and II CC, 11 patients (14%) were ITC+, 29 patients (37%) BMM+. Of these patients, only two demonstrated simultaneous ITC+ /BMM+. The occurrence of BMM+ was neither associated with ITC+ in standard correlation (kappa = − 0.13 [95% confidence interval [CI] = − 0.4–0.14], p = 0.342) nor univariate (odds ratio [OR] = 0.39, 95%CI:0.07–1.50, p = 0.180) or multivariate (OR = 0.58, 95%CI: 0.09–2.95, p = 0.519) analyses. Combined detection of ITC+ /BMM+ demonstrated the poorest overall (HR = 61.60, 95%CI:17.69–214.52, p = 0.032) and recurrence free survival (HR = 61.60, 95%CI: 17.69–214.5, p = 0.032).

Conclusions

These results indicate that simultaneous and not interdependent presence of very early lymphatic and haematologic tumour spread may be considered as a relevant prognostic risk factor for patients with stage I and II CC, thereby suggesting the possible need to reconsider the common assumptions on tumour spread proposed by the prevalent theory of sequential tumour progression.
Alcohol is not associated with increased mortality in adolescent traumatic brain injury patients
Authors: Lu Zachary N. , Yeates Eric O. , Grigorian Areg , Algeo Russell G. , Kuza Catherine M. , Chin Theresa L. , Donnelly Megan , Kong Allen , Nahmias Jeffry
Published: December 2021

Purpose

Compared to adults, there is a paucity of data regarding the association of a positive alcohol screen (PAS) and outcomes in adolescent patients with traumatic brain injury (TBI). We hypothesize adolescent TBI patients with a PAS on admission to have increased mortality compared to patients with a negative alcohol screen.

Methods

The 2017 Trauma Quality Improvement Program database was queried for patients aged 13–17 years presenting with a TBI and serum alcohol screen. Patients with missing information regarding midline shift on imaging and Glasgow Coma Scale (GCS) score were excluded. A multivariable logistic regression analysis for mortality was performed.

Results

From 2553 adolescent TBI patients with an alcohol screen, 220 (8.6%) had a PAS. Median injury severity scores and rates of penetrating trauma (all p > 0.05) were similar between alcohol positive and negative patients. Patients with a PAS had a similar mortality rate (13.2% vs. 12.1%, p = 0.64) compared to patients with a negative screen. Multivariate logistic regression controlling for risk factors associated with mortality revealed a PAS to confer a similar risk of mortality compared to alcohol negative patients (p = 0.40).

Conclusion

Adolescent TBI patients with a PAS had similar associated risk of mortality compared to patients with a negative alcohol screen.
Parameterized Complexity of Directed Spanner Problems
Authors: Fomin Fedor V. , Golovach Petr A. , Lochet William , Misra Pranabendu , Saurabh Saket , Sharma Roohani
Published: December 2021

We initiate the parameterized complexity study of minimum t-spanner problems on directed graphs. For a positive integer t, a multiplicative t-spanner of a (directed) graph G is a spanning subgraph H such that the distance between any two vertices in H is at most t times the distance between these vertices in G, that is, H keeps the distances in G up to the distortion (or stretch) factor t. An additive t-spanner is defined as a spanning subgraph that keeps the distances up to the additive distortion parameter t, that is, the distances in H and G differ by at most t. The task of Directed Multiplicative Spanner is, given a directed graph G with m arcs and positive integers t and k, decide whether G has a multiplicative t-spanner with at most $$m-k$$

m
-
k

arcs. Similarly, Directed Additive Spanner asks whether G has an additive t-spanner with at most $$m-k$$

m
-
k

arcs. We show that (i) Directed Multiplicative Spanner admits a polynomial kernel of size $$\mathcal {O}(k^4t^5)$$

O
(

k
4

t
5

)

and can be solved in randomized $$(4t)^k\cdot n^{\mathcal {O}(1)}$$

(
4
t
)

k

·

n

O
(
1
)

time, (ii) the weighted variant of Directed Multiplicative Spanner can be solved in $$k^{2k}\cdot n^{\mathcal {O}(1)}$$

k

2
k

·

n

O
(
1
)

time on directed acyclic graphs, (iii) Directed Additive Spanner is $${{\,\mathrm{\mathsf{W}}\,}}[1]$$

W

[
1
]

-hard when parameterized by k for every fixed $$t\ge 1$$

t
≥
1

even when the input graphs are restricted to be directed acyclic graphs. The latter claim contrasts with the recent result of Kobayashi from STACS 2020 that the problem for undirected graphs is $${{\,\mathrm{\mathsf{FPT}}\,}}$$

FPT

when parameterized by t and k.
Optimized convolutional neural network architectures for efficient on-device vision-based object detection
Authors: Rodriguez-Conde Ivan , Campos Celso , Fdez-Riverola Florentino
Published: December 2021

Convolutional neural networks have pushed forward image analysis research and computer vision over the last decade, constituting a state-of-the-art approach in object detection today. The design of increasingly deeper and wider architectures has made it possible to achieve unprecedented levels of detection accuracy, albeit at the cost of both a dramatic computational burden and a large memory footprint. In such a context, cloud systems have become a mainstream technological solution due to their tremendous scalability, providing researchers and practitioners with virtually unlimited resources. However, these resources are typically made available as remote services, requiring communication over the network to be accessed, thus compromising the speed of response, availability, and security of the implemented solution. In view of these limitations, the on-device paradigm has emerged as a recent yet widely explored alternative, pursuing more compact and efficient networks to ultimately enable the execution of the derived models directly on resource-constrained client devices. This study provides an up-to-date review of the more relevant scientific research carried out in this vein, circumscribed to the object detection problem. In particular, the paper contributes to the field with a comprehensive architectural overview of both the existing lightweight object detection frameworks targeted to mobile and embedded devices, and the underlying convolutional neural networks that make up their internal structure. More specifically, it addresses the main structural-level strategies used for conceiving the various components of a detection pipeline (i.e., backbone, neck, and head), as well as the most salient techniques proposed for adapting such structures and the resulting architectures to more austere deployment environments. Finally, the study concludes with a discussion of the specific challenges and next steps to be taken to move toward a more convenient accuracy–speed trade-off.
Dynamic portfolio rebalancing through reinforcement learning
Authors: Lim Qing Yang Eddy , Cao Qi , Quek Chai
Published: December 2021

Portfolio managements in financial markets involve risk management strategies and opportunistic responses to individual trading behaviours. Optimal portfolios constructed aim to have a minimal risk with highest accompanying investment returns, regardless of market conditions. This paper focuses on providing an alternative view in maximising portfolio returns using Reinforcement Learning (RL) by considering dynamic risks appropriate to market conditions through dynamic portfolio rebalancing. The proposed algorithm is able to improve portfolio management by introducing the dynamic rebalancing of portfolios with vigorous risk through an RL agent. This is done while accounting for market conditions, asset diversifications, risk and returns in the global financial market. Studies have been performed in this paper to explore four types of methods with variations in fully portfolio rebalancing and gradual portfolio rebalancing, which combine with and without the use of the Long Short-Term Memory (LSTM) model to predict stock prices for adjusting the technical indicator centring. Performances of the four methods have been evaluated and compared using three constructed financial portfolios, including one portfolio with global market index assets with different risk levels, and two portfolios with uncorrelated stock assets from different sectors and risk levels. Observed from the experiment results, the proposed RL agent for gradual portfolio rebalancing with the LSTM model on price prediction outperforms the other three methods, as well as returns of individual assets in these three portfolios. The improvements of the returns using the RL agent for gradual rebalancing with prediction model are achieved at about 27.9–93.4% over those of the full rebalancing without prediction model. It has demonstrated the ability to dynamically adjust portfolio compositions according to the market trends, risks and returns of the global indices and stock assets.
How to improve the assessment of BPM maturity in the era of digital transformation
Authors: Szelągowski Marek , Berniak-Woźny Justyna
Published: December 2021

For almost 30 years, the way of building business process management maturity models (BPM MMs), the importance assigned to individual maturity levels, and the criteria and critical success factors chosen for BPM maturity assessment have not changed significantly, despite the fact that during those three decades, the business environment and organizations themselves have changed enormously. The impact of hyperautomation and the increasing pace of change require the integration of maturity assessment with the BPM implementation methodology, including the repetition of maturity assessment for selected groups of processes. This causes an urgent need to adapt both process maturity assessment methods and BPM MMs to changing working conditions and business requirements. This conceptual paper is based on a model approach. The framework presented in the article continues and at the same time clearly deviates from the tradition of building BPM MMs on the basis of the Capability Maturity Model (CMM). It proposes a two-stage comprehensive process of organizational process maturity assessment, fully integrated into the process of BPM implementation and further business process management. The presented framework makes it possible to assess the process maturity of Industry 4.0 organizations in which dynamic knowledge-intensive business processes (kiBPs) play a key role in creating value.