bluuebunny/crossref_metadata_2025_split huggingface dataset:
Nerve ultrasound studies in POEMS syndrome
Authors: Ding Qingyun , Li Jian , Guan Yuzhou , Wu Shuang , Niu Jingwen , Shen Dongchao , Hu Youfang , Wu Yinmin , Liu Mingsheng , Cui Liying 
Published: February 2021

AbstractIntroductionThe aim of our study was to assess the ultrasonographic features of peripheral nerves in patients with POEMS (polyneuropathy, organomegaly, endocrinopathy, M protein, and skin changes) syndrome.Method34 POEMS syndrome patients and 26 healthy control (HC) participants were recruited prospectively. Cross‐sectional area (CSA) was measured in nerves of limbs, trunks of brachial plexus, and cervical nerve rootsResultsThe CSAs were mildly enlarged at the arm segment of median nerve, elbow segment of ulnar nerve and upper trunk, moderately enlarged at the forearm segment of both median and ulnar nerve, upper trunk of brachial plexus, and C6, C7 cervical nerve roots, and markedly enlarged at the arm segment of ulnar nerve, middle and lower trunk of brachial plexus, as well as C5 cervical root.DiscussionThe CSAs of upper limb nerves were larger in POEMS syndrome patients than in HCs, and the enlargements were most prominent proximally.
A novel pseudo‐polynomial approach for shortest path problems
Authors: Danilovic Milos , Vasiljevic Dragan , Cvetic Biljana 
Published: February 2021

AbstractThis article presents a novel shortest path algorithm for connected networks with nonnegative edge weights. The worst case running time of the single source shortest path version of the algorithm is O(max(m, )) where m is the number of edges of the input network and is the normalized eccentricity of the source vertex vs. The pseudo‐polynomial nature of the time complexity is overcome with a simple speed‐up technique. The proposed approach can be implemented on a wide class of shortest path problems. Approximate solutions can be easily maintained in the preprocessing phase. An experimental efficiency analysis shows that the proposed approach outperforms existing algorithms in total computing time. The proposed algorithm is efficient for all classes of networks and particularly for networks with small diameter.
Tailored higher performance silicone elastomer with nanofibrillated cellulose through acidic treatment
Authors: Mustapha Safarul , Andou Yoshito 
Published: February 2021

AbstractNanofibrillated cellulose (NFC) can be used for reinforcer to silicone polymer to expect enhancement of its mechanical strength. However, NFC is a hydrophilic material, which typically poor‐dispersed characteristic in non‐polar polymer matrices. To overcome this bothersome characteristic, surface modification of NFC has been studied to tailor the interfacial interactions between NFC and matrices for fiber dispersibility in matrices. In this work, NFC was treated with some acids to modify a functional group in NFC. The acid treatment approaches successfully introduced the functional groups onto NFC surface, which confirmed by FT‐IR, TGA, and SEM‐EDS analyses. Moreover, the XRD analysis revealed that this treated NFC was the cellulose type I and acid treatments did not vary it. The TGA results showed lower thermal degradation of all treated NFC as compared to control NFC. Additionally, the effects of treated NFC as nanofiller in the silicone elastomer were evaluated the mechanical properties. The treated NFC also showed a good dispersibility in silicone composite, and no agglomeration was observed. Moreover, the tensile strength and elongation of silicone composite with treated NFC as nanofiller showed high performance compare to silicone composite with pristine NFC. The highest tensile value was recorded at 3.4 MPa in silicone/NFC‐P samples using phosphoric acid‐treated NFC. Therefore, a low concentration of acid treatments has the potential to be an effective method as a surface modification of NFC.
Using machine learning to identify diabetes patients with canagliflozin prescriptions at high‐risk of lower extremity amputation using real‐world data
Authors: Yang Lanting , Gabriel Nico , Hernandez Inmaculada , Winterstein Almut G. , Guo Jingchuan 
Published: February 2021

AbstractAimsCanagliflozin, a sodium‐glucose cotransporter 2 inhibitor indicated for lowering glucose, has been increasingly used in diabetes patients because of its beneficial effects on cardiovascular and renal outcomes. However, clinical trials have documented an increased risk of lower extremity amputations (LEA) associated with canagliflozin. We applied machine learning methods to predict LEA among diabetes patients treated with canagliflozin.MethodsUsing claims data from a 5% random sample of Medicare beneficiaries, we identified 13 904 diabetes individuals initiating canagliflozin between April 2013 and December 2016. The samples were randomly and equally split into training and testing sets. We identified 41 predictor candidates using information from the year prior to canagliflozin initiation, and applied four machine learning approaches (elastic net, least absolute shrinkage and selection operator [LASSO], gradient boosting machine and random forests) to predict LEA risk after canagliflozin initiation.ResultsThe incidence rate of LEA was 0.57% over a median 1.5 years follow‐up. LASSO produced the best prediction, yielding a C‐statistic of 0.81 (95% CI: 0.76, 0.86). Among individuals categorized in the top 5% of the risk score, the actual incidence rate of LEA was 3.74%. Among the 16 factors selected by LASSO, history of LEA [adjusted odds ratio (aOR): 33.6 (13.8, 81.9)] and loop diuretic use [aOR: 3.6 (1.8,7.3)] had the strongest associations with LEA incidence.ConclusionsOur machine learning model efficiently predicted the risk of LEA among diabetes patients undergoing canagliflozin treatment. The risk score may support optimized treatment decisions and thus improve health outcomes of diabetes patients.
Thermal ablation‐insulation performance, microstructural, and mechanical properties of carbon aerogel based lightweight heat shielding composites
Authors: Seraji Mohammad Mehdi , Arefazar Ahmad 
Published: February 2021

AbstractIn this study, carbon aerogel based lightweight composite ablators (CALCAs) with different densities and microstructures were prepared using the vacuum impregnation method. The mechanical strength and morphology of CALCAs were investigated. Ablation‐insulation performance of the samples was also evaluated by an oxyacetylene flame test with a constant heating rate of 2.5 MW/m2. Moreover, the structural evolution during the ablation was studied and the ablation mechanism of CALCAs was proposed. The porous insulators showed good compressive strength (3.2–9 MPa) and low thermal conductivity (lower than 0.35 W/mK). Besides the tunable density, the low recession rate (as low as 0.117 mm/s), and good ablation‐insulation performance (175°C at 25 mm and 125 at 35 mm in‐depth), these lightweight porous heat shielding composites are promising candidates to use as the thermal protection systems for aerospace applications.
Training the next generation of operators: AFPM immersive learning
Authors: Forest Daniel D. 
Published: February 2021

AbstractDemographics of the petroleum refining and petrochemical industries have shown an aging workforce nearing retirement and being replaced by a younger generation of workers who learn and were taught differently. To address the challenge of building competency in the young workforce, the Immersive Learning Committee was created by the American Fuel & Petrochemical Manufacturers (AFPM), a trade association representing nearly all U.S. refining and petrochemical manufacturing capacity. AFPM members produce the fuels that drive the U.S. economy and the chemical building blocks integral to millions of products that make modern life possible. This paper will show how the work of both AFPM and its members is helping bridge the knowledge gap between generations of employees and addressing competency training challenges by developing a digital library of tools—including virtual reality and augmented reality simulations, as well as three‐dimensional assets, and other resources—for broad industry use. The work also assists member companies with their own development of training tools tailored to their unique facilities, processes or company practices. The pilot project, a fired heater training simulation using virtual reality, will be discussed in the paper, as well as a set of leading metrics currently being developed that will help industry understand the effectiveness of the tools.
Synthesis of Chiral CF3‐Contaning Pinane‐Type Hydroxythiols
Authors: Ilchenko Nikita O. , Sudarikov Denis V. , Slepukhin Pavel A. , Rubtsova Svetlana A. , Kutchin Alexandr V. 
Published: February 2021

AbstractFor the first time, the isomeric trifluoromethylated thioacetates have been synthesized in 37–52 % yields by nucleophilic addition of the Ruppert‐Prakash reagent (TMSCF3) to the corresponding thioacetates based on (1R)‐(−)‐myrtenal and (1S)‐(−)‐verbenone. Thioacetates have been transformed into the corresponding pinane thiols in 73–90 % yields. The structure and configuration of the resulting compounds have been determined.
Naphthalimide Assemblies for Simultaneous Detection of Ferrous Ion and H2O2 to Prevent Fenton Reaction
Authors: Kaur Amrit , Kaur Mandeep , Bhalla Vandana , Singh Manroop , Bhanwer A.J.S. , Kumar Manoj 
Published: February 2021

AbstractThe supramolecular assemblies of naphthalimide derivative having morpholine and dihydropyridine units referred as Naph‐MDHP exhibit strong affinity for Fe2+ ions and H2O2 to generate ‘more ordered’ highly fluorescent architectures in aqueous medium. In the presence of supramolecular assemblies of Naph‐MDHP, the oxidation of Fe2+ ions and Fenton reaction is prevented, despite the co‐existence of Fe2+ ions and H2O2 as indicated by slow photocatalytic degradation of dye Methylene blue monitored by UV‐vis spectroscopic studies. The work presented in this manuscript reveals the real time application of naphthalimide assemblies to protect dopamine and DNA against iron‐H2O2 induced oxidative stress.
Greenwaylactams A, B and C, the First Group of Sesquiterpene Alkaloids with an Eight‐Membered Lactam Ring from Greenwayodendron oliveri
Authors: Kemgni Mireille F. , Chenda Laurice Bracine N. , Tchamgoue Joseph , Kenfack Patrice T. , Ngandjui Yvan Anderson T. , Wouamba Steven C. N. , Tiani Gesquière Laure M. , Green Ivan R. , Kouam Simeon F. 
Published: February 2021

AbstractThree new sesquiterpene alkaloids of the polyveoline type containing eight‐membered lactam rings named greenwaylactam A (1), B (2) and C (3) were isolated from the leaves of a Cameroonian medicinal plant Greenwayodendron oliveri (Engl.) Verdc along with three known compounds diacetylpolyveoline (4), N‐acetyl‐8α‐polyveolinone (5) and methyl pheophorbide‐A (6). These comprise the first members of a new class of ξ‐lactam sesquiterpenes. Compounds were isolated by means of successive column chromatographies and their structures were elucidated by extensive NMR spectroscopic analyses and HRESIMS. The configuration of 1 was deduced from its single‐crystal X‐ray diffraction. The crude extract and some isolated compounds were assessed for their antibacterial activity against four enteric bacterial strains Escherichia coli, Salmonelles typhi, Shigella dysenterie and Klebseilla pneumonie using the micro‐dilution method. Compounds 1, 2, 5 and 6 were the most active with MIC values varying between 31.25–250 μg/mL.
Fusing RGB and Thermal Imagery with Channel State Information for Abnormal Activity Detection Using Multimodal Bidirectional LSTM
Authors: Bakalos Nikolaos , Voulodimos Athanasios , Doulamis Nikolaos , Doulamis Anastasios , Papasotiriou Kassiani , Bimpas Matthaios 
Published: February 2021

AbstractIn this paper, we present a multimodal deep model for detection of abnormal activity, based on bidirectional Long Short-Term Memory neural networks (LSTM). The proposed model exploits three different input modalities: RGB imagery, thermographic imagery and Channel State Information from Wi-Fi signal reflectance to estimate human intrusion and suspicious activity. The fused multimodal information is used as input in a Bidirectional LSTM, which has the benefit of being able to capture temporal interdependencies in both past and future time instances, a significant aspect in the discussed unusual activity detection scenario. We also present a Bayesian optimization framework that fine-tunes the Bidirectional LSTM parameters in an optimal manner. The proposed framework is evaluated on real-world data from a critical water infrastructure protection and monitoring scenario and the results indicate a superior performance compared to other unimodal and multimodal approaches and classification models.
Aspects of Hyperscaling Violating geometries at finite cutoff
Authors: Khoeini-Moghaddam Salomeh , Omidi Farzad , Paul Chandrima 
Published: February 2021

Abstract
Recently, it was proposed that a $$ T\overline{T} $$
T

T
¯

deformed CFT is dual to a gravity theory in an asymptotically AdS spacetime at finite radial cutoff. Motivated by this proposal, we explore some aspects of Hyperscaling Violating geometries at finite cutoff and zero temperature. We study holographic entanglement entropy, mutual information (HMI) and entanglement wedge cross section (EWCS) for entangling regions in the shape of strips. It is observed that the HMI shows interesting features in comparison to the very small cutoff case: it is a decreasing function of the cutoff. It is finite when the distance between the two entangling regions goes to zero. The location of its phase transition also depends on the cutoff, and decreases by increasing the cutoff. On the other hand, the EWCS is a decreasing function of the cutoff. It does not show a discontinuous phase transition when the HMI undergoes a first-order phase transition. However, its concavity changes. Moreover, it is finite when the distance between the two strips goes to zero. Furthermore, it satisfies the bound EW ≥ $$ \frac{I}{2} $$

I
2

for all values of the cutoff.
The Cat’s Cradle: deforming the higher rank E1 and $$ {\tilde{E}}_1 $$ theories
Authors: Bergman Oren , Rodríguez-Gómez Diego 
Published: February 2021

Abstract
We use 5-brane webs to study the two-dimensional space of supersymmetric mass deformations of higher rank generalizations of the 5d E1 and $$ {\tilde{E}}_1 $$

E
˜

1

theories. Some of the resulting IR phases are described by IR free supersymmetric gauge theories, while others correspond to interacting fixed points. The number of different phases appears to grow with the rank. The space of deformations is qualitatively different for the even and odd rank cases, but that of the even (odd) rank E1 theory is similar to that of the odd (even) rank $$ {\tilde{E}}_1 $$

E
˜

1

theory. One result of our analysis predicts that the supersymmetric SU(N) theory with CS level k = $$ \frac{N}{2} $$

N
2

+ 4 and a single massless antisymmetric hypermultiplet exhibits an enhanced global symmetry at the UV fixed point, given by SU(2) × SU(2) if N is even, and SU(2) × U(1) if N is odd.
Numerical twist-even SU(1,1)-singlet solutions in open string field theory around the identity-based solution
Authors: Kishimoto Isao , Takahashi Tomohiko 
Published: February 2021

Abstract
Using the level truncation method, we construct numerical solutions, which are twist even and SU(1) singlet, in the theory around the Takahashi-Tanimoto identity-based solution (TT solution) with a real parameter a in the framework of bosonic open string field theory. We find solutions corresponding to “double brane” and “ghost brane” solutions which were constructed by Kudrna and Schnabl in the conventional theory around the perturbative vacuum. Our solutions show somewhat similar a-dependence to tachyon vacuum and single brane solutions, which we found in the earlier works. In this sense, we might be able to expect that they are consistent with the conventional interpretation of a-dependence of the TT solution. We observe that numerical complex solutions at low levels become real ones at higher levels for some region of the parameter a. However, these real solutions do not so improve interpretation for double brane.
Entanglement entropy inequalities in BCFT by holography
Authors: Chou Chia-Jui , Lin Bo-Han , Wang Bin , Yang Yi 
Published: February 2021

Abstract
We study entanglement entropy inequalities in boundary conformal field theory (BCFT) by holographic correspondence. By carefully classifying all the configurations for different phases, we prove the strong subadditiviy and the monogamy of mutual information for holographic entanglement entropy in BCFT at both zero and finite temperatures.
2-Group Symmetries of 6D Little String Theories and T-Duality
Authors: Del Zotto Michele , Ohmori Kantaro 
Published: February 2021

AbstractWe determine the 2-group structure constants for all the six-dimensional little string theories (LSTs) geometrically engineered in F-theory without frozen singularities. We use this result as a consistency check for T-duality: the 2-groups of a pair of T-dual LSTs have to match. When the T-duality involves a discrete symmetry twist, the 2-group used in the matching is modified. We demonstrate the matching of the 2-groups in several examples.
Phase-field gradient theory
Authors: Espath Luis , Calo Victor 
Published: February 2021

AbstractWe propose a phase-field theory for enriched continua. To generalize classical phase-field models, we derive the phase-field gradient theory based on balances of microforces, microtorques, and mass. We focus on materials where second gradients of the phase field describe long-range interactions. By considering a nontrivial interaction inside the body, described by a boundary-edge microtraction, we characterize the existence of a hypermicrotraction field, a central aspect of this theory. On surfaces, we define the surface microtraction and the surface-couple microtraction emerging from internal surface interactions. We explicitly account for the lack of smoothness along a curve on surfaces enclosing arbitrary parts of the domain. In these rough areas, internal-edge microtractions appear. We begin our theory by characterizing these tractions. Next, in balancing microforces and microtorques, we arrive at the field equations. Subject to thermodynamic constraints, we develop a general set of constitutive relations for a phase-field model where its free-energy density depends on second gradients of the phase field. A priori, the balance equations are general and independent of constitutive equations, where the thermodynamics constrain the constitutive relations through the free-energy imbalance. To exemplify the usefulness of our theory, we generalize two commonly used phase-field equations. We propose a ‘generalized Swift–Hohenberg equation’—a second-grade phase-field equation—and its conserved version, the ‘generalized phase-field crystal equation’—a conserved second-grade phase-field equation. Furthermore, we derive the configurational fields arising in this theory. We conclude with the presentation of a comprehensive, thermodynamically consistent set of boundary conditions.
The challenges, approaches, and used techniques of CPS for manufacturing in Industry 4.0: a literature review
Authors: Dafflon Baudouin , Moalla Nejib , Ouzrout Yacine 
Published: February 2021

AbstractThis work aims to review literature related to the latest cyber-physical systems (CPS) for manufacturing in the revolutionary Industry 4.0 for a comprehensive understanding of the challenges, approaches, and used techniques in this domain. Different published studies on CPS for manufacturing in Industry 4.0 paradigms through 2010 to 2019 were searched and summarized. We, then, analyzed the studies at a different granularity level inspecting the title, abstract, and full text to include in the prospective study list. Out of 626 primarily extracted relevant articles, we scrutinized 78 articles as the prospective studies on CPS for manufacturing in Industry 4.0. First, we analyzed the articles’ context to identify the major components along with their associated fine-grained constituents of Industry 4.0. Then, we reviewed different studies through a number of synthesized matrices to narrate the challenges, approaches, and used techniques as the key-enablers of the CPS for manufacturing in Industry 4.0. Although the key technologies of Industry 4.0 are the CPS, Internet of Things (IoT), and Internet of Services (IoS), the human component (HC), cyber component (CC), physical component (PC), and their HC-CC, CC-PC, and HC-PC interfaces need to be standardized to achieve the success of Industry 4.0.
Sharp Error Term in Local Limit Theorems and Mixing for Lorentz Gases with Infinite Horizon
Authors: Pène Françoise , Terhesiu Dalia 
Published: February 2021

AbstractWe obtain sharp error rates in the local limit theorem for the Sinai billiard map (one and two dimensional) with infinite horizon. This result allows us to further obtain higher order terms and thus, sharp mixing rates in the speed of mixing of dynamically Hölder observables for the planar and tubular infinite horizon Lorentz gases in the map (discrete time) case. We also obtain an asymptotic estimate for the tail probability of the first return time to the initial cell. In the process, we study families of transfer operators for infinite horizon Sinai billiards perturbed with the free flight function and obtain higher order expansions for the associated families of eigenvalues and eigenprojectors.
Manufacture of all-wood sawdust-based particle board using ionic liquid-facilitated fusion process
Authors: Orelma Hannes , Tanaka Atsushi , Vuoriluoto Maija , Khakalo Alexey , Korpela Antti 
Published: February 2021

AbstractTraditional particle board can generate harmful indoor air emissions due to the volatile resin-based compounds present. This study investigated the preparation of sawdust particle board using the novel ionic liquid based fusion approach with [EMIM]OAc. The dissolution parameters were investigated using the thermal optical microscopy technique. The particle board sheets were prepared by hot pressing sawdust in the presence of ionic liquid (IL) ([EMIM]OAc) and subsequently purifying the fusion sawdust matrix from the IL with methanol. The fusion process of the sawdust particles was analysed with SEM and mechanical testing. The raw materials and the produced materials were investigated with elemental analysis, FTIR, and 13C-SS-NMR. IL fusion of the sawdust required a temperature above 150 °C, similar to the glass transition temperature (tg) of lignin. At lower temperatures, strong particle fusion was not obtained. It was observed that the sawdust/IL weight ratio was an important parameter of the fusion process, and a 1:3 weight ratio resulted in the strongest particle boards with a tensile strength of up to 10 MPa, similar to commercial particle boards. The particle fusion process was also studied with a twin-screw extruder. The extrusion enhanced the fusion of the sawdust particles by increasing dissolution of the sawdust particles, which was subsequently seen in elevated tensile strength (20 MPa). The study provides a practical view of how sawdust-based particle board can be manufactured using ionic liquid-based fusion.