bluuebunny/crossref_metadata_2025_split huggingface dataset:
Éducation Thérapeutique du Patient (ETP) dans la maladie d’Alzheimer et les maladies apparentées en France : état des lieux et retours d’expérience
Authors: Derollez Céline , Loreaux Aude , Mahée Diane , Thévenet Marie , Pasquier Florence , Cassagnaud Pascaline 
Published: April 2023

Introduction : L’Éducation Thérapeutique du Patient (ETP) fait partie des approches non médicamenteuses proposées aux patients atteints de maladie d’Alzheimer et maladies apparentées (MA2). Elle est recommandée par la Haute Autorité de santé et les plans Alzheimer mais reste peu développée. Objectifs : Nos objectifs sont (i) exposer l’offre d’ETP s’adressant à ces patients en France, (ii) recueillir les retours d’expérience des professionnels de santé, patients et aidants impliqués, (iii) décrire les difficultés rencontrées et les pistes proposées. Méthode : Nous avons répertorié les programmes d’ETP validés par les Agences Régionales de Santé (ARS) s’adressant aux patients atteints de MA2, ayant réalisé au moins un cycle d’ETP. Les retours d’expérience ont été recueillis par entretiens semi-dirigés. Résultats : Parmi les 49 programmes validés par les ARS, 30 répondaient à nos critères. Nous avons constaté une grande hétérogénéité territoriale, organisationnelle et clinique. Établir un schéma d’ETP classique auprès d’une population atteinte de troubles cognitifs s’avère complexe, néanmoins les équipes s’adaptent. Conclusion : Notre travail souligne la dimension psycho-sociale de l’ETP dans le parcours de soin des patients atteints de MA2. Son développement reste un défi et doit être facilité via une coordination des équipes et une harmonisation des pratiques portées entre autres par la Fédération des Centres Mémoire (FCM).
Robotic-assisted Gynecological Surgery in Older Patients – a Comparative Cohort Study of Perioperative Outcomes
Authors: Mothes Anke R. , Kather Angela , Cepraga Irina , Esber Anke , Kwetkat Anja , Runnebaum Ingo B. 
Published: April 2023

Abstract
Study design Because of current demographic developments, a hypothesis was proposed whereby older female patients aged > 65 years can be safely operated using minimally invasive,
robotic-assisted surgery, despite having more preoperative comorbidities. A comparative cohort study was designed to compare the age group ≥ 65 years (older age group, OAG) with the age
group < 65 years (younger age group, YAG) after robotic-assisted gynecological surgery (RAS) in two German centers.
Patients and methods Consecutive RAS procedures performed between 2016 and 2021 at the Women’s University Hospital of Jena and the Robotic Center Eisenach to treat benign or
oncological indications were included in the study. The age groups were compared according to their preoperative comorbidities (ASA, Charlson comorbidity index [CCI], cumulative illness
rating scale – geriatric version [CIRS-G]) and perioperative parameters such as Clavien-Dindo (CD) classification of surgical complications. Analysis was performed using Welch’s
t-test, chi2 test, and Fisher’s exact test.
Results A total of 242 datasets were identified, of which 63 (73 ± 5 years) were OAG and 179 were YAG (48 ± 10 years). Patient characteristics and the percentage of benign or
oncological indications did not differ between the two age groups. Comorbidity scores and the percentage of obese patients were higher in the OAG group: CCI (2.7 ± 2.0 vs. 1.5 ± 1.3;
p < 0.001), CIRS-G (9.7 ± 3.9 vs. 5.4 ± 2.9; p < 0.001), ASA class II/III (91.8% vs. 74.1%; p = 0.004), obesity (54.1% vs. 38.2%; p = 0.030). There was no difference between age
groups, even grouped for benign or oncological indications, with regard to perioperative parameters such as duration of surgery (p = 0.088; p = 0.368), length of hospital stay (p = 0.786;
p = 0.814), decrease in Hb levels (p = 0.811; p = 0.058), conversion rate (p = 1.000; p = 1.000) and CD complications (p = 0.433; p = 0.745).
Conclusion Although preoperative comorbidity was higher in the group of older female patients, no differences were found between age groups with regard to perioperative outcomes
following robotic-assisted gynecological surgery. Patient age is not a contraindication for robotic gynecological surgery.
Synthesis of (±)-Phyltetralin by Cu/Pd-Catalyzed Arylboration
Authors: Trammel Grace L. , Kerlin Abby C. , Brown M. Kevin , Zachau Christian 
Published: April 2023

AbstractA synthesis of (±)-phyltetralin is reported. Notable features of the synthesis include a diastereoselective Cu/Pd-catalyzed arylboration reaction and a Matteson homologation.
Incidence and Risk Factors for the Development of New-Onset Diabetes after Kidney Transplantation
Authors: Elamouri Jamila S. 
Published: April 2023

Abstract
Objective New-onset diabetes mellitus after transplantation (NODAT), also known as posttransplant diabetes mellitus, is a common complication after kidney transplantation. It is associated with an increased risk of graft failure and death. Therefore, minimizing the risk of NODAT is a priority after kidney transplantation. This study aimed to determine the incidence of NODAT, the risk factors for its development, and the therapeutic drugs used for its management.
Patients and Methods This is an observational, retrospective study on kidney recipients who were followed up in our center in 2021. After excluding known diabetic patients, second transplant patients, and those with follow-up periods less than 6 months, 308 recipients were included in the study. Demographic, clinical, and laboratory data were collected from the patient records. The patients were categorized as diabetic or nondiabetic.
Results All patients' mean age was 35.9±11.6 years (standard deviation). The male-to-female ratio was 2.13:1. The overall incidence of NODAT was 38.3%. The median time to NODAT diagnosis was 6 months. Patients older than 40 were more likely to develop NODAT (61.1%; p = 0.000). The prevalence of pretransplant body mass index (BMI) more than 25 was significantly higher (67.6%) in diabetic than among nondiabetic patients (p = 0.000). NODAT patients were more likely to have had a rejection episode (65 vs. 35% in nondiabetic patients; p = 0.011). A high trough level of calcineurin inhibitors carried a significant risk of NODAT development. Tacrolimus trough level more than or equal to 10 ng/mL had an odds ratio of 57.9 (95% confidence interval [CI] 7.689–1262.2; p = 0.0007) for the development of NODAT. Likewise, a cyclosporine-A trough level more than or equal to 150 ng/mL had an odds ratio of 100.7 (95% CI: 7.31–4293.5; p = 0.0028).
Conclusion NODAT incidence was high in this study. Older age, high BMI, prior rejection episode, steroid dose, and high calcineurin inhibitors trough levels were significant risk factors for developing NODAT.
Toward quantification of hypoxia using fluorinated Eu
II/III
-containing ratiometric probes
Authors: Subasinghe S. A. Amali S. , Ortiz Caitlyn J. , Romero Jonathan , Ward Cassandra L. , Sertage Alexander G. , Kurenbekova Lyazat , Yustein Jason T. , Pautler Robia G. , Allen Matthew J. 
Published: April 2023

Hypoxia is a prognostic biomarker of rapidly growing cancers, where the extent of hypoxia is an indication of tumor progression and prognosis; therefore, hypoxia is also used for staging while performing chemo- and radiotherapeutics for cancer. Contrast-enhanced MRI using Eu
II
-based contrast agents is a noninvasive method that can be used to map hypoxic tumors, but quantification of hypoxia using these agents is challenging due to the dependence of signal on the concentration of both oxygen and Eu
II
. Here, we report a ratiometric method to eliminate concentration dependence of contrast enhancement of hypoxia using fluorinated Eu
II/III
-containing probes. We studied three different Eu
II/III
couples of complexes containing 4, 12, or 24 fluorine atoms to balance fluorine signal-to-noise ratio with aqueous solubility. The ratio between the longitudinal relaxation time (
T
1
) and
19
F signal of solutions containing different ratios of Eu
II
- and Eu
III
-containing complexes was plotted against the percentage of Eu
II
-containing complexes in solution. We denote the slope of the resulting curves as hypoxia indices because they can be used to quantify signal enhancement from Eu, that is related to oxygen concentration, without knowledge of the absolute concentration of Eu. This mapping of hypoxia was demonstrated in vivo in an orthotopic syngeneic tumor model. Our studies significantly contribute toward improving the ability to radiographically map and quantify hypoxia in real time, which is critical to the study of cancer and a wide range of diseases.
Identification of acoustic point sources in a two-layered medium from multi-frequency sparse far field patterns
Authors: Liu Xiaodong , Shi Qingxiang 
Published: April 2023

Abstract
We consider the reconstruction of point sources in a two layered medium from the multi-frequency sparse far field patterns taken on the upper half sphere. The point sources are located in both the upper half space and the lower half space, and consequently bring difficulty for the inverse problem because of the combination of two different types of far field patterns. After establishing the uniqueness of the point sources by the multi-frequency far field patterns at properly chosen sparse observation directions, we introduce a multi-step numerical scheme for identifying all the points sources. Numerical examples show that the proposed sampling methods work very well for locating the positions and the formulas for determining the corresponding scattering strengths are valid and stable with respect to the noises.
Robust pure spin currents in a binuclear ferric phthalocyanine junction driven by the photogalvanic effect
Authors: Zhang Bo , Tao Bairui , Li Hua , Liu Xiaojie , Wang Yin , Yin Haitao 
Published: April 2023

Abstract
The investigation of optical methods for generating pure spin current at the molecular level is of critical importance. We investigated the spin-related photocurrent produced by the photogalvanic effect in a binuclear ferric phthalocyanine (Fe2Pc2) junction with spatial inversion symmetry. When the magnetic moment directions of Fe atoms at the center of each phthalocyanine are in parallel configuration (PC) or antiparallel configuration (APC), the molecular junction exhibits different photoresponses. In contrast to the PC, which lacks both charge and spin current, the APC produces pure spin current. Additionally, the pure spin current exhibits robustness with respect to polarization type and polarization angle. This difference in characteristics between the PC and APC stems from the different symmetry of their spin densities, which can be altered by the direction of the magnetic moments of two Fe atoms at the center of the molecule.
Current and deformation induced by voltage in the single LiNi0.8Co0.1Mn0.1O2 particle from atomic force microscopy technique and phase field simulation
Authors: Wang Miao , Zhu Zhe , Liu Yao 
Published: April 2023

Abstract
One of the key factors affecting lithium-ion battery electrode materials’ efficiency is the process of lithiation and delithiation. Studies of the electrochemical behavior of Ni-rich active electrode materials at the nanoscale have largely been focused on macroscopic measurements, but few have investigated the intrinsic microscopic mechanism underlying their failure. In this paper, lithium-ion diffusion current and surface deformation of single LiNi0.8Co0.1Mn0.1O2 (NCM811) nanoparticles under external electric fields were measured by atomic force microscopy (AFM) techniques. Then, the current and deformation of NCM811 single particle under the applied voltage were simulated by phase field method to analyze electrochemical behaviors of the particle from experiments based on the electrochemical-mechanical coupled model. The simulation results revealed that the change of lithium-ion concentration and stress in particles are the factors leading to the evolution of current and deformation under applied voltage observed by AFM.
Structure shape measurement method based on an optical fiber shape sensor
Authors: Tian Yuqi , Dang Hong , Liu Wenya , Cui Jiwen , Li Yang , Tan Jiubin 
Published: April 2023

AbstractIn industry and architecture, real-time and complete measurement of structures has become a research frontier since it is directly related to the safety of life and property. Optical fibers have the potential to monitor constructions due to advantages such as small size, anti-electromagnetic interference, etc. However, existing research on optical fiber sensors pays attention to the sensing fiber itself and ignores the layout of the optical fibers. As a result, currently available fiber sensors are only suitable for monitoring one-dimensional rigid structures such as surgical robots and puncture needles. They may face challenges when measuring the freeform surfaces encountered in industrial and architectural scenarios. In this paper, a cross-orthogonal measurement method based on optical fiber shape sensors is proposed to meet the shape measurement requirements of freeform surfaces. The cross-orthogonal network allows global measurement and performs surface reconstructions more easily as compared to single-fiber arrays. It also divides the sensing fiber into several segments that are reconstructed separately (with different initial frames), avoiding the cumulative error at the end of the sensing fiber. Results of verification experiments using four-core fibers indicate that the presented method can improve measurement accuracy.
Adaptive soft sensor design using a regression neural network and bias update strategy for non-linear industrial processes
Authors: Vijayan S Venkata , Mohanta Hare K , Rout Bijay K , Pani Ajaya Kumar 
Published: April 2023

Abstract
Soft sensing of quality parameters in process industries has been an active area of research for the past two decades. To improve the performance of soft sensors in the scenario of time varying process states, adaptation capability is incorporated into the soft sensor model. In this work, recursive (R), sliding window (SW) and just-in-time learning (JITL) frameworks are used for adaptive soft sensor design. A rarely explored modeling technique in the adaptation framework, the generalized regression neural network (GRNN) is used as a local modeling strategy. A bias update procedure is applied during the model adaptation activity to improve the prediction accuracy. Further, the performances of the developed models are tested against input–output data dimension mismatch along with various concept drift phenomena by considering a different number of labeled samples for inputs and outputs. The proposed adaptation strategy is applied on two benchmark industrial processes. Simulation results show that the GRNN local modeling approach combined with the bias update strategy gives higher prediction accuracy than other adaptive soft sensors proposed in the literature. Moreover, GRNN local modeling strategy using SW adaptation mechanism has the least computation time among the three adaptation methods due to the use of a low number of samples for model development.
Roadmap on thermoelectricity
Authors: Artini Cristina , Pennelli Giovanni , Graziosi Patrizio , Li Zhen , Neophytou Neophytos , Melis Claudio , Colombo Luciano , Isotta Eleonora , Lohani Ketan , Scardi Paolo , Castellero Alberto , Baricco Marcello , Palumbo Mauro , Casassa Silvia , Maschio Lorenzo , Pani Marcella , Latronico Giovanna , Mele Paolo , Di Benedetto Francesca , Contento Gaetano , De Riccardis Maria Federica , Fucci Raffaele , Palazzo Barbara , Rizzo Antonella , Demontis Valeria , Prete Domenic , Isram Muhammad , Rossella Francesco , Ferrario Alberto , Miozzo Alvise , Boldrini Stefano , Dimaggio Elisabetta , Franzini Marcello , Galliano Simone , Barolo Claudia , Mardi Saeed , Reale Andrea , Lorenzi Bruno , Narducci Dario , Trifiletti Vanira , Milita Silvia , Bellucci Alessandro , Trucchi Daniele M 
Published: April 2023

Abstract
The increasing energy demand and the ever more pressing need for clean technologies of energy conversion pose one of the most urgent and complicated issues of our age. Thermoelectricity, namely the direct conversion of waste heat into electricity, is a promising technique based on a long-standing physical phenomenon, which still has not fully developed its potential, mainly due to the low efficiency of the process. In order to improve the thermoelectric performance, a huge effort is being made by physicists, materials scientists and engineers, with the primary aims of better understanding the fundamental issues ruling the improvement of the thermoelectric figure of merit, and finally building the most efficient thermoelectric devices. In this Roadmap an overview is given about the most recent experimental and computational results obtained within the Italian research community on the optimization of composition and morphology of some thermoelectric materials, as well as on the design of thermoelectric and hybrid thermoelectric/photovoltaic devices.
Lasing mode manipulation in a Benz-shaped GaN cavity via the Joule effect of individual Ni wires
Authors: Qin Feifei , Ji Xin , Yang Ying , Li Meng , Li Xin , Lin Yi , Lu Kerui , Wang Ru , Wang Xiaoxuan , Wang Yongjin , Zhu Gangyi 
Published: April 2023

Abstract
Silicon-based gallium nitride lasers are considered potential laser sources for on-chip integration. However, the capability of on-demand lasing output with its reversible and wavelength tunability remains important. Herein, a Benz-shaped GaN cavity is designed and fabricated on a Si substrate and coupled to a Ni metal wire. Under optical pumping, excitation position-related lasing and exciton combination properties of pure GaN cavity are studied systematically. Under electrically driven, joule thermal of Ni metal wire makes it easy to change the temperature of the cavity. And then, we demonstrate a joule heat-induced contactless lasing mode manipulation in the coupled GaN cavity. The driven current, coupling distance, and excitation position influence the wavelength tunable effect. Compared with other positions, the outer ring position has the highest lasing properties and lasing mode tuning abilities. The optimized structures demonstrate clear wavelength tuning and an even mode switch. The thermal reduction of the band gap is identified to account for the modification of the lasing profile, but the thermo-optic effect is non-negligible under a high-driven current.
Synthesis of non-planar graphene-wrapped copper nanoparticles with iron(III) oxide decoration for high performance supercapacitors
Authors: Chu Hsuan-I , Ho Hsiao-Yun , Huang Yi-June , Tsai Dung-Sheng , Lee Chuan-Pei 
Published: April 2023

Abstract
The performance of supercapacitors strongly depends on the electrochemical characterizations of electrode materials. Herein, a composite material consisted of iron(III) oxide (Fe2O3) and multilayer graphene-wrapped copper nanoparticles (Fe2O3/MLG-Cu NPs) is fabricated on a flexible carbon cloth (CC) substrate via two-step synthesis process for supercapacitor application. Where, MLG-Cu NPs are prepared on CC by one-step chemical vapor deposition synthesis approach; thereafter, the Fe2O3 is further deposited on the MLG-Cu NPs/CC via successive ionic layer adsorption and reaction method. The related material characterizations of Fe2O3/MLG-Cu NPs are well investigated by scanning electron microscopic, high resolution transmission electron microscopy), Raman spectrometer and X-ray photoelectron spectroscopy; the electrochemical behaviors of the pertinent electrodes are studied by cyclic voltammogram, galvanostatic charge/discharge (GCD) and electrochemical impedance spectroscopy measurements. The flexible electrode with Fe2O3/MLG-Cu NPs composites exhibits the best specific capacitance of 1092.6 mF cm−2 at 1 A g−1, which is much higher than those of electrodes with Fe2O3 (863.7 mF cm−2), MLG-Cu NPs (257.4 mF cm−2), multilayer graphene hollow balls (MLGHBs, 14.4 mF cm−2) and Fe2O3/MLGHBs (287.2 mF cm−2). Fe2O3/MLG-Cu NPs electrode also exhibits an excellent GCD durability, and its capacitance remains 88% of its original value after 5000 cycles of the GCD process. Finally, a supercapacitor system consisted of four Fe2O3/MLG-Cu NPs/CC electrodes can efficiently power various light-emitting diodes (i.e. red, yellow, green, and blue lights), demonstrating the practical application of Fe2O3/MLG-Cu NPs/CC electrode.
Multi-level fusion network for mild cognitive impairment identification using multi-modal neuroimages
Authors: Xu Haozhe , Zhong Shengzhou , Zhang Yu 
Published: April 2023

Abstract

Objective. Mild cognitive impairment (MCI) is a precursor to Alzheimer’s disease (AD) which is an irreversible progressive neurodegenerative disease and its early diagnosis and intervention are of great significance. Recently, many deep learning methods have demonstrated the advantages of multi-modal neuroimages in MCI identification task. However, previous studies frequently simply concatenate patch-level features for prediction without modeling the dependencies among local features. Also, many methods only focus on modality-sharable information or modality-specific features and ignore their incorporation. This work aims to address above-mentioned issues and construct a model for accurate MCI identification. Approach. In this paper, we propose a multi-level fusion network for MCI identification using multi-modal neuroimages, which consists of local representation learning and dependency-aware global representation learning stages. Specifically, for each patient, we first extract multi-pair of patches from multiple same position in multi-modal neuroimages. After that, in the local representation learning stage, multiple dual-channel sub-networks, each of which consists of two modality-specific feature extraction branches and three sine-cosine fusion modules, are constructed to learn local features that preserve modality-sharable and modality specific representations simultaneously. In the dependency-aware global representation learning stage, we further capture long-range dependencies among local representations and integrate them into global ones for MCI identification. Main results. Experiments on ADNI-1/ADNI-2 datasets demonstrate the superior performance of the proposed method in MCI identification tasks (Accuracy: 0.802, sensitivity: 0.821, specificity: 0.767 in MCI diagnosis task; accuracy: 0.849, sensitivity: 0.841, specificity: 0.856 in MCI conversion task) when compared with state-of-the-art methods. The proposed classification model has demonstrated a promising potential to predict MCI conversion and identify the disease-related regions in the brain. Significance. We propose a multi-level fusion network for MCI identification using multi-modal neuroimage. The results on ADNI datasets have demonstrated its feasibility and superiority.