bluuebunny/crossref_metadata_2025 huggingface dataset:
High Pressure Rapid Synthesis of LiCrTiO4 with Oxygen Vacancy for High Rate Lithium‐Ion Battery Anodes
Authors: Yan Lv , Qin Jieming , Liang Benkuan , Gao Shanlin , Wang Bo , Cui Jiuyue , Bolag Altan , Yang Yanchun
Published: August 2022

Lithium‐ion battery based on LiCrTiO4 (LCTO) is considered to be a promising anode material, as they provide higher safety and durability beyond than that of graphite electrode. However, the applications of this transformative technology demand improved inherent electrical conductivity of LCTO as well as a simple and rapid synthetic route. Here, LCTO with oxygen vacancies (OVs) is fabricated using high‐pressure synthesis technology in only 40 min. The optimal synthesis pressure is 0.8 GPa (LCTO‐0.8). The reversible capacity of LCTO‐0.8 at 1C is 131 mA h g−1 after 1000 cycles and the capacity retention is nearly 97%, and the reversible capacity of LCTO synthesized at atmospheric pressure (LCTO‐P) is 85 mA h g−1 under the same circumstances. Even at 5C, the reversible capacity is 110 mA h g−1, which is 77% higher than LCTO‐P. Furthermore, it is confirmed by theoretical calculations that the introduction of OVs has the occupation of electronic states at the Fermi level, which greatly enhances the intrinsic conductivity of LCTO. Specifically, the electronic conductivity has increased by two orders of magnitude compared with LCTO‐P. Therefore, high‐pressure synthesis technology endows LCTO with superior characteristics, providing a new avenue for industrialization.
Effects of Si on the Ductile‐to‐Brittle Transition Behavior of As‐Cast Advanced High‐Strength Steels
Authors: Giacomin Rafael Coura , Bollinger Andrea Lynn , Komolwit Piyamanee , Natarajan Thinium T. , Pistorius Petrus Christiaan , Webler Bryan A.
Published: August 2022

High Si concentrations in third‐generation advanced high‐strength steels (AHSS) are known to cause cracking in continuous cast slabs during cooling at temperatures below 300 °C. To investigate the mechanism connecting Si to this embrittlement, impact toughness tests are conducted on as‐cast Fe–0.2C–3.0Mn steels with 0.5, 1.5, and 3.0 wt% Si at temperatures between 100 and 400 °C. The propagation path of the cracks through the microstructure of the specimens is examined. The ductile‐to‐brittle transition (DBT) behaviors of the three steels are compared. Higher Si concentrations raise the DBT temperature of the steels. The influence of Si on both solid‐solution strengthening and autotempering during cooling likely contributes to this by increasing the hardness of these as‐cast microstructures. In addition, the precipitation of pro‐eutectoid ferrite (αPE), which is promoted by higher Si concentrations, significantly lowers the upper shelf energy of the DBT curve. The αPE phase also alters the propagation path of brittle fracture in the specimens, potentially contributing to the increase in DBT temperature. The increase in DBT temperature and decrease in upper shelf energy may contribute to the as‐cast AHSS slab embrittlement at low temperatures observed in the industry.
Experimental methods for the analysis of the tensile behavior of concrete joints
Authors: Höffgen Jan P. , Mohs Matthias , Sonderegger Eric , Malárics‐Pfaff Viktória , Dehn Frank
Published: August 2022

Adhesion plays an important role in the evaluation of hydraulic structures with unreinforced concrete joints. The experimental determination of joint tensile strength as a quantifiable parameter is not standardized, resulting in a variety of test setups found in literature. The present paper highlights advantages and disadvantages of three of the most common tension tests for plain concrete and concrete joints through both theoretical and laboratory experimental analysis on specimens with artificial joints. Splitting tension tests were found to be inexpensive but tend to overestimate the adhesive strength of weak joints. Direct tension tests require an elaborate test setup but may yield information on the tension softening behavior. Pull‐off tests stand out for their ability to yield in‐situ results but deliver inconclusive results.
Engineering gold nanoparticles for molecular diagnostics and biosensing
Authors: Oliveira Beatriz B. , Ferreira Daniela , Fernandes Alexandra R. , Baptista Pedro Viana
Published: August 2022

Advances in nanotechnology and medical science have spurred the development of engineered nanomaterials and nanoparticles with particular focus on their applications in biomedicine. In particular, gold nanoparticles (AuNPs) have been the focus of great interest, due to their exquisite intrinsic properties, such as ease of synthesis and surface functionalization, tunable size and shape, lack of acute toxicity and favorable optical, electronic, and physicochemical features, which possess great value for application in biodetection and diagnostics purposes, including molecular sensing, photoimaging, and application under the form of portable and simple biosensors (e.g., lateral flow immunoassays that have been extensively exploited during the current COVID‐19 pandemic). We shall discuss the main properties of AuNPs, their synthesis and conjugation to biorecognition moieties, and the current trends in sensing and detection in biomedicine and diagnostics.

This article is categorized under:

Diagnostic Tools > Biosensing

Diagnostic Tools > In Vitro Nanoparticle‐Based Sensing

Diagnostic Tools > In Vivo Nanodiagnostics and Imaging
Neural Network Robustness as a Verification Property: A Principled Case Study
Authors: Casadio Marco , Komendantskaya Ekaterina , Daggitt Matthew L. , Kokke Wen , Katz Guy , Amir Guy , Refaeli Idan
Published: August 2022

Neural networks are very successful at detecting patterns in noisy data, and have become the technology of choice in many fields. However, their usefulness is hampered by their susceptibility to adversarial attacks. Recently, many methods for measuring and improving a network’s robustness to adversarial perturbations have been proposed, and this growing body of research has given rise to numerous explicit or implicit notions of robustness. Connections between these notions are often subtle, and a systematic comparison between them is missing in the literature. In this paper we begin addressing this gap, by setting up general principles for the empirical analysis and evaluation of a network’s robustness as a mathematical property—during the network’s training phase, its verification, and after its deployment. We then apply these principles and conduct a case study that showcases the practical benefits of our general approach.
Affine Loop Invariant Generation via Matrix Algebra
Authors: Ji Yucheng , Fu Hongfei , Fang Bin , Chen Haibo
Published: August 2022

Loop invariant generation, which automates the generation of assertions that always hold at the entry of a while loop, has many important applications in program analysis and formal verification. In this work, we target an important category of while loops, namely affine while loops, that are unnested while loops with affine loop guards and variable updates. Such a class of loops widely exists in many programs yet still lacks a general but efficient approach to invariant generation. We propose a novel matrix-algebra approach to automatically synthesizing affine inductive invariants in the form of an affine inequality. The main novelty of our approach is that (i) the approach is general in the sense that it theoretically addresses all the cases of affine invariant generation over an affine while loop, and (ii) it can be efficiently automated through matrix-algebra (such as eigenvalue, matrix inverse) methods.

The details of our approach are as follows. First, for the case where the loop guard is a tautology (i.e., ‘true’), we show that the eigenvalues and their eigenvectors of the matrices derived from the variable updates of the loop body encompass all meaningful affine inductive invariants. Second, for the more general case where the loop guard is a conjunction of affine inequalities, our approach completely addresses the invariant-generation problem by first establishing through matrix inverse the relationship between the invariants and a key parameter in the application of Farkas’ lemma, then solving the feasible domain of the key parameter from the inductive conditions, and finally illustrating that a finite number of values suffices for the key parameter w.r.t a tightness condition for the invariants to be generated.

Experimental results show that compared with previous approaches, our approach generates much more accurate affine inductive invariants over affine while loops from existing and new benchmarks within a few seconds, demonstrating the generality and efficiency of our approach.
Data-driven Numerical Invariant Synthesis with Automatic Generation of Attributes
Authors: Bouajjani Ahmed , Boutglay Wael-Amine , Habermehl Peter
Published: August 2022

We propose a data-driven algorithm for numerical invariant synthesis and verification. The algorithm is based on the ICE-DT schema for learning decision trees from samples of positive and negative states and implications corresponding to program transitions. The main issue we address is the discovery of relevant attributes to be used in the learning process of numerical invariants. We define a method for solving this problem guided by the data sample. It is based on the construction of a separator that covers positive states and excludes negative ones, consistent with the implications. The separator is constructed using an abstract domain representation of convex sets. The generalization mechanism of the decision tree learning from the constraints of the separator allows the inference of general invariants, accurate enough for proving the targeted property. We implemented our algorithm and showed its efficiency.
Abstraction Modulo Stability for Reverse Engineering
Authors: Becchi Anna , Cimatti Alessandro
Published: August 2022

The analysis of legacy systems requires the automated extraction of high-level specifications. We propose a framework, called Abstraction Modulo Stability, for the analysis of transition systems operating in stable states, and responding with run-to-completion transactions to external stimuli. The abstraction captures the effects of external stimuli on the system state, and describes it in the form of a finite state machine. This approach is parametric on a set of predicates of interest and the definition of stability. We consider some possible stability definitions which yield different practically relevant abstractions, and propose a parametric algorithm for abstraction computation. The obtained FSM is extended with guards and effects on a given set of variables of interest. The framework is evaluated in terms of expressivity and adequacy within an industrial project with the Italian Railway Network, on reverse engineering tasks of relay-based interlocking circuits to extract specifications for a computer-based reimplementation.
Reachability of Koopman Linearized Systems Using Random Fourier Feature Observables and Polynomial Zonotope Refinement
Authors: Bak Stanley , Bogomolov Sergiy , Hencey Brandon , Kochdumper Niklas , Lew Ethan , Potomkin Kostiantyn
Published: August 2022

Koopman operator linearization approximates nonlinear systems of differential equations with higher-dimensional linear systems. For formal verification using reachability analysis, this is an attractive conversion, as highly scalable methods exist to compute reachable sets for linear systems. However, two main challenges are present with this approach, both of which are addressed in this work. First, the approximation must be sufficiently accurate for the result to be meaningful, which is controlled by the choice ofobservable functionsduring Koopman operator linearization. By using random Fourier features as observable functions, the process becomes more systematic than earlier work, while providing a higher-accuracy approximation. Second, although the higher-dimensional system is linear, simple convex initial sets in the original space can become complex non-convex initial sets in the linear system. We overcome this using a combination of Taylor model arithmetic and polynomial zonotope refinement. Compared with prior work, the result is more efficient, more systematic and more accurate.
STLmc: Robust STL Model Checking of Hybrid Systems Using SMT
Authors: Yu Geunyeol , Lee Jia , Bae Kyungmin
Published: August 2022

We present theSTLmcmodel checker for signal temporal logic (STL) properties of hybrid systems. TheSTLmctool can perform STL model checking up to a robustness threshold for a wide range of hybrid systems. Our tool utilizes the refutation-complete SMT-based bounded model checking algorithm by reducing the robust STL model checking problem into Boolean STL model checking. IfSTLmcdoes not find a counterexample, the system is guaranteed to be correct up to the given bounds and robustness threshold. We demonstrate the effectiveness ofSTLmcon a number of hybrid system benchmarks.
Shared Certificates for Neural Network Verification
Authors: Fischer Marc , Sprecher Christian , Dimitrov Dimitar Iliev , Singh Gagandeep , Vechev Martin
Published: August 2022

Existing neural network verifiers compute a proof that each input is handled correctly under a given perturbation by propagating a symbolic abstraction of reachable values at each layer. This process is repeated from scratch independently for each input (e.g., image) and perturbation (e.g., rotation), leading to an expensive overall proof effort when handling an entire dataset. In this work, we introduce a new method for reducing this verification cost without losing precision based on a key insight that abstractions obtained at intermediate layers for different inputs and perturbations can overlap or contain each other. Leveraging our insight, we introduce the general concept of shared certificates, enabling proof effort reuse across multiple inputs to reduce overall verification costs. We perform an extensive experimental evaluation to demonstrate the effectiveness of shared certificates in reducing the verification cost on a range of datasets and attack specifications on image classifiers including the popular patch and geometric perturbations. We release our implementation at https://github.com/eth-sri/proof-sharing.
Methode zur abstrakten Modellierung von Automotive Systems-on-Chips
Authors: Kirchner Aljoscha
Published: August 2022

Im folgenden Kapitel wird das Konzept der in dieser Arbeit entwickelten Entwicklungsmethode zur abstrakten Modellierung von Automotive Systems-on-Chips vorgestellt. Teile der Methode sowie eine Zusammenfassung der Entwicklungsmethode wurden bereits in den Arbeiten [76], [77], [78] und [79] veröffentlicht. Das übergeordnete Ziel der Methode ist hierbei die Steigerung der Effizienz über alle Phasen der SoC-Entwicklung hinweg.
Zusammenfassung und Ausblick
Authors: Kirchner Aljoscha
Published: August 2022

Im folgenden Kapitel wird die hier vorliegende Arbeit zusammengefasst. Dazu wird auf die in dieser Arbeit vorgestellte modellbasierte Entwicklungsmethode eingegangen. Zudem werden die daraus resultierenden Ergebnisse in gekürzter Form dargestellt.
M5-branes wrapped on four-dimensional orbifolds
Authors: Cheung K. C. Matthew , Fry Jacob H. T. , Gauntlett Jerome P. , Sparks James
Published: August 2022

Abstract

We construct supersymmetric AdS3 solutions of D = 11 supergravity, dual to d = 2, $$ \mathcal{N} $$
N
= (0, 2) SCFTs, that are associated with M5-branes wrapping two different four-dimensional orbifolds. In one case the orbifold is a spindle fibred over another spindle, while in the other it is a spindle fibred over a Riemann surface with genus g > 1. We show that the central charges of the d = 2 SCFTs calculated from the gravity solutions agree with field theory computations using anomaly polynomials. The new D = 11 solutions are obtained after constructing a new consistent Kaluza-Klein truncation of maximal D = 7 gauged supergravity reduced on a spindle down to D = 5 minimal gauged supergravity.
Genetic basis of sorghum leaf width and its potential as a surrogate for transpiration efficiency
Authors: Zhi Xiaoyu , Hammer Graeme , Borrell Andrew , Tao Yongfu , Wu Alex , Hunt Colleen , van Oosterom Erik , Massey-Reed Sean Reynolds , Cruickshank Alan , Potgieter Andries B. , Jordan David , Mace Emma , George-Jaeggli Barbara
Published: August 2022

Key message

Leaf width was correlated with plant-level transpiration efficiency and associated with 19 QTL in sorghum, suggesting it could be a surrogate for transpiration efficiency in large breeding program.

Enhancing plant transpiration efficiency (TE) by reducing transpiration without compromising photosynthesis and yield is a desirable selection target in crop improvement programs. While narrow individual leaf width has been correlated with greater intrinsic water use efficiency in C4 species, the extent to which this translates to greater plant TE has not been investigated. The aims of this study were to evaluate the correlation of leaf width with TE at the whole-plant scale and investigate the genetic control of leaf width in sorghum. Two lysimetry experiments using 16 genotypes varying for stomatal conductance and three field trials using a large sorghum diversity panel (n = 701 lines) were conducted. Negative associations of leaf width with plant TE were found in the lysimetry experiments, suggesting narrow leaves may result in reduced plant transpiration without trade-offs in biomass accumulation. A wide range in width of the largest leaf was found in the sorghum diversity panel with consistent ranking among sorghum races, suggesting that environmental adaptation may have a role in modifying leaf width. Nineteen QTL were identified by genome-wide association studies on leaf width adjusted for flowering time. The QTL identified showed high levels of correspondence with those in maize and rice, suggesting similarities in the genetic control of leaf width across cereals. Three a priori candidate genes for leaf width, previously found to regulate dorsoventrality, were identified based on a 1-cM threshold. This study provides useful physiological and genetic insights for potential manipulation of leaf width to improve plant adaptation to diverse environments.
Risk Assessment and Hazardous Effects of Metal Contamination in O. niloticus and S. galilaeus from Four Islands of the River Nile
Authors: Elhaddad Engy , Salaah Sally M. , Salama Hanan M. M. , El-Sherif Dina M. , Gaber Hanan S.
Published: August 2022

The Nile River islands are recognized as the most productive lands in Egypt. Although, these islands are vulnerable to several natural and man-made crises. The present study was aimed to evaluate the consequences of different anthropogenic activities on the heavy metals load and histological alterations inO. niloticusandS. galilaeuscollected from four different Nile River islands along the Great Cairo sector (Egypt), and the possible health risks for human consumers. Metals were accumulated in both fish muscles in the following order: Fe > Zn > Cu > Mn > Pb.S. galilaeuswas recorded higher metal pollution index thanO. niloticus, while El-Warrak Island was documented the highest MPI and hazard quotient among all sampling sites. All sampled tissues were recorded histopathological lesions in both fish. The present study may be considered as an early alert for habitual consumers, particularly at high consumption rates of some fish species.
Body-Ordered Approximations of Atomic Properties
Authors: Thomas Jack , Chen Huajie , Ortner Christoph
Published: August 2022

We show that the local density of states (LDOS) of a wide class of tight-binding models has a weak body-order expansion. Specifically, we prove that the resulting body-order expansion for analytic observables such as the electron density or the energy has an exponential rate of convergence both at finite Fermi-temperature as well as for insulators at zero Fermi-temperature. We discuss potential consequences of this observation for modelling the potential energy landscape, as well as for solving the electronic structure problem.
Percutaneous autologous bone marrow concentrate for knee osteoarthritis: patient-reported outcomes and progenitor cell content
Authors: Centeno Christopher J. , Berger Dustin R. , Money Brandon T. , Dodson Ehren , Urbanek Christopher W. , Steinmetz Neven J.
Published: August 2022

Purpose

Knee osteoarthritis (OA) is a common, progressively debilitating joint disease, and the intra-articular injection of autologous bone marrow concentrate (BMC) may offer a minimally invasive method of harnessing the body’s own connective tissue progenitor cells to counteract accompanying degenerative effects of the disease. However, the extent to which the progenitor cell content of BMC influences treatment outcomes is unclear. We sought to determine whether patient-reported outcome measures associated with BMC treatment for knee OA are related to the concentration of progenitor cells provided.

Methods

In the present study, 65 patients (72 knees) underwent treatment for knee OA with autologous BMC and self-reported their outcomes for up to one year using follow-up questionnaires tracking function, pain, and percent improvement. A small fraction of each patient’s BMC sample was reserved for quantification with a haematological analyzer and cryopreserved for subsequent analysis of potential connective tissue progenitor cells using a colony-forming unit fibroblast (CFU-F) assay.

Results

Patients reported significant increases in function and overall percent improvement in addition to decreases in pain relative to baseline levels following treatment with autologous BMC that persisted through 12 months. Patients reporting improved outcomes (46 of 72 knees) received BMC injections having higher CFU-F concentrations than non-responding patients (21.1×103 ± 12.4×103 vs 14.3×103 ± 7.0 x103 CFU-F per mL). A progenitor cell concentration of 18×103 CFU-F per mL of BMC was found to best differentiate responders from non-responders.

Conclusion

This study provides supportive evidence for using autologous BMC in the minimally invasive treatment of knee OA and suggests that increased progenitor cell content leads to improved treatment outcomes.

Trial registration

ClinicalTrials.gov Identifier: NCT03011398, 1/7/17
Legal obligation in the general population: face mask influence on endophthalmitis after intravitreal injection
Authors: Neubauer Jonas , Gklavas Konstantinos , Kortüm Friederike , Gosheva Mariya , Bartz-Schmidt Karl Ulrich , Ziemssen Focke
Published: August 2022

Purpose

To investigate whether compulsory face masking in public life changes the incidence or pattern of post-injection endophthalmitis (PIE).

Patients and methods

All injections of bevacizumab, ranibizumab, aflibercept, dexamethasone or triamcinolone between 01/01/2015 and 12/31/2021 at the University Eye Clinic of Tuebingen were included in this retrospective analysis. The injection procedure itself was unchanged since 2015 and included the use of a sterile drape covering the head up to the shoulders which prevents airflow toward the eye. Furthermore, all staff wore a face mask and gloves at all times. The two study periods were defined by the introduction of a compulsory face masking rule in public life (01/01/2015 until 04/27/2020 vs. 04/28/2020 until 12/31/2021).

Results

A total of 83,543 injections were performed in the tertiary eye clinic, associated with a total of 20 PIE (0.024%, 1/4177 injections). Of these, thirteen PIE were documented during the pre-pandemic period (0.021%, 1/4773 injections) and seven PIE during the pandemic period (0.033%, 1/3071 injections). No significant difference in PIE risk was observed (p = 0.49), and there was no case of oral flora associated PIE.

Conclusion

Although some potential confounders (wearing time, skin flora) could not be considered, there was no clear signal that the introduction of compulsory face masking in public life did alter the risk for PIE in our patient population. Three and six months after PIE, no difference in visual acuity was detectable between the two study periods.
Origin of thyrotropin-releasing hormone neurons that innervate the tuberomammillary nuclei
Authors: Sánchez-Jaramillo Edith , Wittmann Gábor , Menyhért Judit , Singru Praful , Gómez-González Gabriela B. , Sánchez-Islas Eduardo , Yáñez-Recendis Nashiely , Pimentel-Cabrera Jaime Arturo , León-Olea Martha , Gereben Balázs , Fekete Csaba , Charli Jean-Louis , Lechan Ronald M.
Published: August 2022

Hypophysiotropic thyrotropin-releasing hormone (TRH) neurons function as metabolic sensors that regulate the thyroid axis and energy homeostasis. Less is known about the role of other hypothalamic TRH neurons. As central administration of TRH decreases food intake and increases histamine in the tuberomammillary nuclei (TMN), and TMN histamine neurons are densely innervated by TRH fibers from an unknown origin, we mapped the location of TRH neurons that project to the TMN. The retrograde tracer, cholera toxin B subunit (CTB), was injected into the TMN E1–E2, E4–E5 subdivisions of adult Sprague–Dawley male rats. TMN projecting neurons were observed in the septum, preoptic area, bed nucleus of the stria terminalis (BNST), perifornical area, anterior paraventricular nucleus, peduncular and tuberal lateral hypothalamus (TuLH), suprachiasmatic nucleus and medial amygdala. However, CTB/pro-TRH178-199 double-labeled cells were only found in the TuLH. The specificity of the retrograde tract-tracing result was confirmed by administering the anterograde tracer, Phaseolus vulgaris leuco-agglutinin (PHAL) into the TuLH. Double-labeled PHAL-pro-TRH boutons were identified in all subdivisions of the TMN. TMN neurons double-labeled for histidine decarboxylase (Hdc)/PHAL, Hdc/Trh receptor (Trhr), and Hdc/Trh. Further confirmation of a TuLH-TRH neuronal projection to the TMN was established in a transgenic mouse that expresses Cre recombinase in TRH-producing cells following microinjection of a Cre recombinase-dependent AAV that expresses mCherry into the TuLH. We conclude that, in rodents, the TRH innervation of TMN originates in part from TRH neurons in the TuLH, and that this TRH population may contribute to regulate energy homeostasis through histamine Trhr-positive neurons of the TMN.
How can counselling by family physicians on nutrition and physical activity be improved: trends from a survey in Germany
Authors: Boesenecker S. J. , Mathies V. , Buentzel J. , Huebner J.
Published: August 2022

Purpose

Cancer and its therapy causes severe symptoms, most of which are amendable to nutrition and physical activity (PA). Counselling on nutrition and PA empowers patients to take part more actively in their treatment. Many cancer patients are yet in need of information on these topics. In this study, we investigate the perception of family physicians (FP) on nutrition and PA in cancer patient care and assess barriers and steps to improve their involvement in counselling on these topics.

Methods

Based on qualitative content analysis of 5 semi-structured interviews with FP, a questionnaire was developed and completed by 61 German FP.

Results

Most of the FP acknowledged the importance of nutrition and PA during (91.4%) and after (100%) cancer therapy. While many participants were involved in cancer patient care, 65.6% of FP viewed themselves as primary reference person to address these topics. However, a third (32.8%) of FP were unfamiliar with information thereof. Some were unsatisfied regarding timely updates on their patient’s treatment course via discharge letters (25.0%) or phone calls (36.2%). FP would like to dedicate more consultation time addressing nutrition and PA than they currently do (p < 0.001).

Conclusion

Communication btween healthcare practitioners about mutual cancer patient’s treatment must be improved, e.g. utilising electronic communication to quicken correspondence. Acquisition of information on nutrition and PA in cancer patient care needs to be facilitated for FP, approachable by compiling reliable information and their sources. Involvement of FP in structured treatment programs could benefit cancer patient care.

Trial registration number

(May 7, 2021): 2021–2149-Bef.
The Brittle–Ductile Transition and the Formation of Compaction Bands in the Savonnières Limestone: Impact of the Stress and Pore Fluid
Authors: Sari Mustafa , Sarout Joel , Poulet Thomas , Dautriat Jeremie , Veveakis Manolis
Published: August 2022

Carbonate sediments play a prominent role on the global geological stage as they store more than $$60\%$$

60
%

of world’s oil and $$40\%$$

40
%

of world’s gas reserves. Prediction of the deformation and failure of porous carbonates is, therefore, essential to minimise reservoir compaction, fault reactivation, or wellbore instability. This relies on our understanding of the mechanisms underlying the observed inelastic response to fluid injection or deviatoric stress perturbations. Understanding the impact of deformation/failure on the hydraulic properties of the rock is also essential as injection/production rates will be affected. In this work, we present new experimental results from triaxial deformation experiments carried out to elucidate the behaviour of a porous limestone reservoir analogue (Savonnières limestone). Drained triaxial and isotropic compression tests were conducted at five different confining pressures in dry and water-saturated conditions. Stress–strain data and X-ray tomography images of the rock indicate two distinct types of deformation and failure regimes: at low confinement (10 MPa) brittle failure in the form of dilatant shear banding was dominant; whereas at higher confinement compaction bands orthogonal to the maximum principal stress formed. In addition to the pore pressure effect, the presence of water in the pore space significantly weakened the rock, thereby shrinking the yield envelope compared to the dry conditions, and shifted the brittle–ductile transition to lower effective confining pressures (from 35 MPa to 29 MPa). Finally, permeability measurements during deformation show a reduction of an order of magnitude in the ductile regime due to the formation of the compaction bands. These results highlight the importance of considering the role of the saturating fluid in the brittle–ductile response of porous rocks and elucidate some of the microstructural processes taking place during this transition.
Fast-SEC coupled to ICP-MS for selected metal determination and its stability over time in polish wine
Authors: Fabjanowicz Magdalena , Płotka-Wasylka Justyna
Published: August 2022

Metal ions contribute to the wine browning (as reaction catalysts), turbidity (in complexes), and astringency (due to interaction with tannins). Being aware that bioavailability and metabolism of metal ions in the human body are strictly related with their concentration and the form they occur it is important to monitor not only the total content of metals but also their speciation. Thus, we can obtain more information about their potential toxicity to human health. Present research shows the application of fast size exclusion chromatography (Fast-SEC) coupled to ICP-MS for the evaluation of the distribution of elements in different sized complexes in Polish wine. The study was focused on the selected ten elements (Al, B, Ba, Cu, Fe, Mn, Ni, Pb, Sr, Zn). Additional information of this work was the evaluation of the metal complex stability over time. Based on the obtained results, it can be seen that metal complexes present in the studied wine samples are stable even 10 months after the wine bottle opening.

Graphical abstract
Survival trends in gastric cancer patients between 1987 and 2016: a population-based cohort study in Finland
Authors: Maharjan Urgena , Kauppila Joonas H.
Published: August 2022

Background

Gastric cancer is the fourth leading cause of cancer-related deaths globally. There is a paucity of national studies examining gastric cancer mortality in relation to treatment status. This study evaluated the survival trends in gastric adenocarcinoma and all gastric cancers stratified by treatment in Finland during 1987–2016.

Methods

This population-based, nationwide, retrospective cohort study included all gastric cancer patients registered in the Finnish Cancer Registry and Patient Registry. The survival rates were calculated for 1, 3, and 5 years, stratified by treatment. Prognostic factors were determined using Cox regression.

Results

A total of 18,713 non-cardia gastric adenocarcinoma, and 3617 cardia adenocarcinoma patients were included. Surgical treatment decreased for non-cardia adenocarcinoma and remained constant for cardia adenocarcinoma. In non-cardia adenocarcinoma, the 5-year survival declined from 17% to 16% from 1987–1991 to 2012–2016. In surgically treated patients, survival increased from 29% to 38%, while an increase from 4% to 7% in those undergoing chemotherapy and decrease from 6% to 3% in those not receiving any treatment were observed. In cardia adenocarcinoma, the 5-year survival increased from 10% to 18% in all patients, 16% to 40% in surgical patients, 0% to 5% in patients receiving chemotherapy, and from 5% to 9% in patients receiving no treatment. Earlier calendar periods, older age, male sex, and higher comorbidity were risk factors for poor prognosis.

Conclusions

Gastric non-cardia adenocarcinoma survival declined, limited to advanced stage patients not receiving any treatment. Gastric cardia cancer survival seems to have improved over time in Finland.

Mini abstract

This study evaluated survival trends of gastric cancer in Finland during 1987–2016 and established that the 5-year survival is declining in non-cardia adenocarcinoma but improving in all gastric cancers.
Excess Savings Are Recession-Specific and Compensatory: Evidence From the US
Authors: Voinea Liviu , Loungani Prakash
Published: August 2022

There is a consensus among academics and policymakers that the excess savings built up by households during the past couple of years are specific to the pandemic. Based on data from the past half century for the US, this article shows that savings generally increase during recessions; the pandemic is different only by the magnitude of these savings, but not by their sign. Moreover, it suggests that these excess savings are rather compensatory than precautionary, as households save more to rebuild their lost wealth.
Ukraine’s EU Integration: A Long Way Home
Authors: Sologoub Ilona
Published: August 2022

It is time to admit that while Russia remains an empire and has nuclear weapons, it will always be an existential threat to democracies.
Fragility analysis of structural pounding between adjacent structures arranged in series with various alignment configurations under near-field earthquakes
Authors: Ebrahimiyan Fahimeh , Hadianfard Mohammad Ali , Naderpour Hosein , Jankowski Robert
Published: August 2022

A major cause of local to total damages is related to structural pounding in a large number of past earthquakes. In general, these collisions take place as a result of differences in the dynamic characteristics of the colliding structures. To acquire a better perception of the behavior of structures, in this paper, three structures featuring different heights are modeled in series and with various configurations next to each other in OpenSees. To determine the collision effects of the structures, three different configurations of 4-, 8- and 12-story adjacent reinforced concrete special moment resisting frames were considered. Then, by conducting an incremental dynamic analysis, their structural seismic limit state capacities were assessed via 20 near-field record subsets recommended by FEMA-P695. At last, for the above adjacent buildings with various separation distances and configurations, the fragility curves were determined, and the probability of exceedance from the primary Hazus-MH failure criteria was estimated. In addition, the results were compared with those obtained when this phenomenon did not take place for buildings to have a better perception of the pounding phenomenon. The results of the analyses show that arranging adjacent structures in series greatly affects the collapse capacities of the colliding structures. In addition, in the case when the shorter structure is placed in the middle of two taller structures, it results in the most critical situation among all configurations, and in this case, a higher reduction is observed in the structural performance levels.
Fetal Brain Damage in Human Fetuses with Congenital Cytomegalovirus Infection: Histological Features and Viral Tropism
Authors: Piccirilli Giulia , Gabrielli Liliana , Bonasoni Maria Paola , Chiereghin Angela , Turello Gabriele , Borgatti Eva Caterina , Simonazzi Giuliana , Felici Silvia , Leone Marta , Salfi Nunzio Cosimo Mario , Santini Donatella , Lazzarotto Tiziana
Published: August 2022

Human cytomegalovirus (HCMV) causes congenital neurological lifelong disabilities. To date, the neuropathogenesis of brain injury related to congenital HCMV (cCMV) infection is poorly understood. This study evaluates the characteristics and pathogenetic mechanisms of encephalic damage in cCMV infection. Ten HCMV-infected human fetuses at 21 weeks of gestation were examined. Specifically, tissues from different brain areas were analyzed by: (i) immunohistochemistry (IHC) to detect HCMV-infected cell distribution, (ii) hematoxylin–eosin staining to evaluate histological damage and (iii) real-time PCR to quantify tissue viral load (HCMV-DNA). The differentiation stage of HCMV-infected neural/neuronal cells was assessed by double IHC to detect simultaneously HCMV-antigens and neural/neuronal markers: nestin (a marker of neural stem/progenitor cells), doublecortin (DCX, marker of cells committed to the neuronal lineage) and neuronal nuclei (NeuN, identifying mature neurons). HCMV-positive cells and viral DNA were found in the brain of 8/10 (80%) fetuses. For these cases, brain damage was classified as mild (n = 4, 50%), moderate (n = 3, 37.5%) and severe (n = 1, 12.5%) based on presence and frequency of pathological findings (necrosis, microglial nodules, microglial activation, astrocytosis, and vascular changes). The highest median HCMV-DNA level was found in the hippocampus (212 copies/5 ng of human DNA [hDNA], range: 10–7,505) as well as the highest mean HCMV-infected cell value (2.9 cells, range: 0–23), followed by that detected in subventricular zone (1.7 cells, range: 0–19). These findings suggested a preferential viral tropism for both neural stem/progenitor cells and neuronal committed cells, residing in these regions, confirmed by the expression of DCX and nestin in 94% and 63.3% of HCMV-positive cells, respectively. NeuN was not found among HCMV-positive cells and was nearly absent in the brain with severe damage, suggesting HCMV does not infect mature neurons and immature neural/neuronal cells do not differentiate into neurons. This could lead to known structural and functional brain defects from cCMV infection.

Graphical Abstract
Styler: learning formatting conventions to repair Checkstyle violations
Authors: Loriot Benjamin , Madeiral Fernanda , Monperrus Martin
Published: August 2022

Ensuring the consistent usage of formatting conventions is an important aspect of modern software quality assurance. To do so, the source code of a project should be checked against the formatting conventions (or rules) adopted by its development team, and then the detected violations should be repaired if any. While the former task can be automatically done by format checkers implemented in linters, there is no satisfactory solution for the latter. Manually fixing formatting convention violations is a waste of developer time and code formatters do not take into account the conventions adopted and configured by developers for the used linter. In this paper, we present Styler, a tool dedicated to fixing formatting rule violations raised by format checkers using a machine learning approach. For a given project, Styler first generates training data by injecting violations of the project-specific rules in violation-free source code files. Then, it learns fixes by feeding long short-term memory neural networks with the training data encoded into token sequences. Finally, it predicts fixes for real formatting violations with the trained models. Currently, Styler supports a single checker, Checkstyle, which is a highly configurable and popular format checker for Java. In an empirical evaluation, Styler repaired 41% of 26,791 Checkstyle violations mined from 104 GitHub projects. Moreover, we compared Styler with the IntelliJ plugin CheckStyle-IDEA and the machine-learning-based code formatters Naturalize and CodeBuff. We found out that Styler fixes violations of a diverse set of Checkstyle rules (24/25 rules), generates smaller repairs in comparison to the other systems, and predicts repairs in seconds once trained on a project. Through a manual analysis, we identified cases in which Styler does not succeed to generate correct repairs, which can guide further improvements in Styler. Finally, the results suggest that Styler can be useful to help developers repair Checkstyle formatting violations.
Optimal priority assignment for real-time systems: a coevolution-based approach
Authors: Lee Jaekwon , Shin Seung Yeob , Nejati Shiva , Briand Lionel C.
Published: August 2022

In real-time systems, priorities assigned to real-time tasks determine the order of task executions, by relying on an underlying task scheduling policy. Assigning optimal priority values to tasks is critical to allow the tasks to complete their executions while maximizing safety margins from their specified deadlines. This enables real-time systems to tolerate unexpected overheads in task executions and still meet their deadlines. In practice, priority assignments result from an interactive process between the development and testing teams. In this article, we propose an automated method that aims to identify the best possible priority assignments in real-time systems, accounting for multiple objectives regarding safety margins and engineering constraints. Our approach is based on a multi-objective, competitive coevolutionary algorithm mimicking the interactive priority assignment process between the development and testing teams. We evaluate our approach by applying it to six industrial systems from different domains and several synthetic systems. The results indicate that our approach significantly outperforms both our baselines, i.e., random search and sequential search, and solutions defined by practitioners. Our approach scales to complex industrial systems as an offline analysis method that attempts to find near-optimal solutions within acceptable time, i.e., less than 16 hours.
The Importance of Understanding Deep Learning
Authors: Räz Tim , Beisbart Claus
Published: August 2022

Some machine learning models, in particular deep neural networks (DNNs), are not very well understood; nevertheless, they are frequently used in science. Does this lack of understanding pose a problem for using DNNs to understand empirical phenomena? Emily Sullivan has recently argued that understanding with DNNs is not limited by our lack of understanding of DNNs themselves. In the present paper, we will argue, contra Sullivan, that our current lack of understanding of DNNs does limit our ability to understand with DNNs. Sullivan’s claim hinges on which notion of understanding is at play. If we employ a weak notion of understanding, then her claim is tenable, but rather weak. If, however, we employ a strong notion of understanding, particularly explanatory understanding, then her claim is not tenable.
Probabilistic solvers enable a straight-forward exploration of numerical uncertainty in neuroscience models
Authors: Oesterle Jonathan , Krämer Nicholas , Hennig Philipp , Berens Philipp
Published: August 2022

Understanding neural computation on the mechanistic level requires models of neurons and neuronal networks. To analyze such models one typically has to solve coupled ordinary differential equations (ODEs), which describe the dynamics of the underlying neural system. These ODEs are solved numerically with deterministic ODE solvers that yield single solutions with either no, or only a global scalar error indicator on precision. It can therefore be challenging to estimate the effect of numerical uncertainty on quantities of interest, such as spike-times and the number of spikes. To overcome this problem, we propose to use recently developed sampling-based probabilistic solvers, which are able to quantify such numerical uncertainties. They neither require detailed insights into the kinetics of the models, nor are they difficult to implement. We show that numerical uncertainty can affect the outcome of typical neuroscience simulations, e.g. jittering spikes by milliseconds or even adding or removing individual spikes from simulations altogether, and demonstrate that probabilistic solvers reveal these numerical uncertainties with only moderate computational overhead.
Attention-based advantage actor-critic algorithm with prioritized experience replay for complex 2-D robotic motion planning
Authors: Zhou Chengmin , Huang Bingding , Hassan Haseeb , Fränti Pasi
Published: August 2022

Robotic motion planning in dense and dynamic indoor scenarios constantly challenges the researchers because of the motion unpredictability of obstacles. Recent progress in reinforcement learning enables robots to better cope with the dense and unpredictable obstacles by encoding complex features of the robot and obstacles into the encoders like the long-short term memory (LSTM). Then these features are learned by the robot using reinforcement learning algorithms, such as the deep Q network and asynchronous advantage actor critic algorithm. However, existing methods depend heavily on expert experiences to enhance the convergence speed of the networks by initializing them via imitation learning. Moreover, those approaches based on LSTM to encode the obstacle features are not always efficient and robust enough, therefore sometimes causing the network overfitting in training. This paper focuses on the advantage actor critic algorithm and introduces an attention-based actor critic algorithm with experience replay algorithm to improve the performance of existing algorithm from two perspectives. First, LSTM encoder is replaced by a robust encoder attention weight to better interpret the complex features of the robot and obstacles. Second, the robot learns from its past prioritized experiences to initialize the networks of the advantage actor-critic algorithm. This is achieved by applying the prioritized experience replay method, which makes the best of past useful experiences to improve the convergence speed. As results, the network based on our algorithm takes only around 15% and 30% experiences to get rid of the early-stage training without the expert experiences in cases with five and ten obstacles, respectively. Then it converges faster to a better reward with less experiences (near 45% and 65% of experiences in cases with ten and five obstacles respectively) when comparing with the baseline LSTM-based advantage actor critic algorithm. Our source code is freely available at the GitHub (https://github.com/CHUENGMINCHOU/AW-PER-A2C).