bluuebunny/crossref_metadata_2025_split huggingface dataset:
Trans‐spatial Structure Additive Passivated Sn(II) for High‐efficiency CsSnI3 Perovskite Solar Cells Fabricated in Humid Air
Authors: Li Xinrui , Zhou Huanyi , Zhang Junfang , Sang Kaihang , Fan Hua , Lu Jiangying , Pang Qi , Chen Peican , Zhou Liya , Li Lei , Yang Yunfan 
Published: December 2022

AbstractBlack crystalline γ‐CsSnI3 is an ideal light absorption material to replace lead‐based perovskite due to its low biotoxicity and excellent photoelectric properties. However, CsSnI3 is usually prepared in a low humidity inert atmosphere because of its oxidation in air. The severe preparation environment, on the other hand, will surely raise the economic cost of mass production. Therefore, a kind of additive engineering is proposed to introduce (1R, 2R)‐(−)‐1,2‐diaminocyclohexane (transDACH), a small nitrogen‐containing ligand with trans‐spatial structure, into the perovskite layer, which can stabilize Sn2+ in the preparation process, allowing for the preparation of efficient and stable perovskite solar cells under high humidity conditions. The forward scan maximum power conversion efficiency (PCE) of the CsSnI3‐transDACH device reaches 5.49%, the highest for hole‐free carbon‐based CsSnI3 PSCs prepared in humid air conditions. Furthermore, the transDACH‐modified devices retain 73.7% of their original PCEs after 160 hours of storage in ambient air conditions.
Is whole‐body magnetic resonance imaging a source of anxiety in oncological patients?
Authors: Mazzocco Ketti , Busacchio Derna , Summers Paul Eugene , Marzorati Chiara , Pricolo Paola , Petralia Giuseppe , Pravettoni Gabriella 
Published: December 2022

AbstractObjectiveMagnetic resonance often produces feelings of anxiety before, or during, the examination. The aim of this study was to assess anxiety and potential causes of anxiety in cancer patients undergoing whole‐body magnetic resonance imaging (WB‐MRI).MethodsThis monocentric study recruited 70 cancer patients who were scheduled to undergo WB‐MRI for detection, staging or therapy monitoring. At baseline (prior to the WB‐MRI), assessments were performed using the State–Trait Anxiety Inventory (STAI‐Y 1), Illness Perception Questionnaire (IPQ‐R), Big Five Inventory (BIF‐10) and Revised Life Orientation Test (LOT‐R), while at the end of the WB‐MRI examination the patients repeated the STAI‐Y 1 questionnaire and were asked to indicate their preference between WB‐MRI and computed tomography.ResultsWe found a positive correlation between pre‐ and post‐examination STAI‐Y 1 scores (r = 0.536, p < .0001), with no significant difference between them. Pre‐examination STAI‐Y 1 scores had a negative correlation with the emotional stability in the BIF‐10 questionnaire (r = −0.47, p = .001) and a positive correlation with emotional representation (r = 0.57, p = .001) in IPQ‐R. The post‐examination STAI‐Y 1 had a negative correlation with optimistic orientation (r = −0.59, p = .001).ConclusionsThe anxiety associated with a WB‐MRI examination was only in small part associated with the examination itself, and in fact, most patients preferred WB‐MRI to computed tomography. Concern with the outcome of the examination was likely a greater source of anxiety.
Prognostic factors of toxicity of immune checkpoint inhibitors in nonsmall cell lung cancer and small cell lung cancer patients: The ToxImmune study
Authors: Difoum Francoise , Schernberg Antoine , Vanquaethem Hélène , Picchi Hugo , Roy Audrey Le , Vuagnat Perrine , Helissey Carole 
Published: December 2022

AbstractBackgroundImmunotherapy alone or in combination has clearly improved the survival of patients with lung cancer. However, it may also be responsible for adverse events impacting these patients' quality of life. The ToxImmune study aims to identify prognostic factors that can help to predict immune‐related adverse events.MethodsWe included all patients aged 18 years and older who had received at least one dose of immune checkpoint inhibitors, with or without other therapy, between June 2015 and December 2020 and were diagnosed with nonsmall cell lung cancer or small‐cell lung cancer. Patients' baseline demographic characteristics, biological blood markers, and imaging by PET‐scanner were collected from electronic medical records. All adverse events (AEs) and immune‐related AEs (irAEs) were recorded (Common Terminology Criteria For Adverse Events V.5.0).ResultsSixty‐four patients were included, of whom 60 (94%) presented at least one irAE. The incidence of Common Terminology Criteria for Adverse Events (CTCAE) grade 2 and grade 3–4 was 34% and 8% respectively.Female sex, Primitive Tumor Standardized Uptake Value Max (SUVmax) <5, number of metastases ≥3 and immunotherapy received after the first line were found to be significant risk factors for immune‐related adverse events. Based on the number of risk factors, the ToxImmune score predicts the risk of having a grade ≥2 adverse event (primitive tumor SUV ≥ 5 = 0 vs. primitive tumor SUV <5 = 1, number of metastases <3 = 0 vs. number of metastases ≥3 = 1 and L1 = 0 vs. L1 ≥ 1). The incidence of grade ≥2 adverse events was 20%, 55% and 90% with ToxImmune scores 0, 1 and = 2 respectively (p = .003). Median progression‐free survival (PFS) times were 19.2 months, 6.64 months and 2.63 months for ToxImmune scores 0, 1 and = 2 respectively, p = .13. Median overall survival times were 22.6 months, 16.4 months and 9.8 months for ToxImmune scores 0, 1 and ≥2 respectively, p = .24. The disease control rate (DRR) was 78% in ToxIummune score 0 group, and 50% in ToxImmune score 1 and ≥2 groups (p = .363).ConclusionThe ToxImmune score, which is grounded on objective clinical parameters, indicates that cases with a high score had an advanced threat of severe adverse events. The ToxImmune score could therefore be used in clinical practice to identify patients treated for lung cancer with immunotherapy and at risk of severe AE.
“Struck down by cancer with no old life to fall back on” a clinical study of illness experiences among Norwegian adolescent and young adult cancer survivors investigating the ethical implications of their illness narratives
Authors: Hjulstad Kristine , Bondevik Hilde , Hem Marit Helene , Nortvedt Per 
Published: December 2022

AbstractBackgroundCancer is a leading cause of death among people 15–24 years of age. Increasing numbers of cancer patients survive. Extensive cancer therapy may cause wide‐ranging somatic and psychosocial challenges in the lives of the survivors.Research indicates adolescent and young adult cancer (AYA) survivors need to be seen as a distinctive group of survivors having unique health care needs. The existing literature suggests the need for specific follow‐up care programs addressing the challenges of AYAs and providing them access to specialized after care, as well as a need to explore AYA cancer survivors' own illness experiences.AimsThrough the theoretical lens of narrative medicine and care ethics, our purpose was to investigate the particular challenges encountered by the AYA cancer survivors, and how they view themselves in light of their illness experiences. We ask how AYA cancer survivors are met and understood by their medical professionals?MethodsThis study applied a qualitative method using a narrative research design by collecting self‐stories of illness in order to conceptualize human experiences of illness among AYA cancer survivors. Eight in‐depth interviews were conducted using a narrative analysis according to the narrative plots ofrestitution,chaosandquest,as suggested by Arthur Frank.ResultsHopelessness and a struggle to take part in the activities of daily life as survivors of cancer were revealed. Too ill to fully take part in the society, the AYA cancer survivors strive to be understood for what they are, namely young survivors.ConclusionThe survivors'stories reveal a moral imperative that needs to be honored by medical professionals in order to improve cancer care. Cancer survivorship may be a lifelong process necessitating long‐term follow‐up care. With the lack of specific care programs for AYA cancer survivors, follow‐up care is provided by general practitioners or other medical professionals, who often lack expertise in the unique challenges faced by AYA survivors. Because they feel their needs are unmet and their stories not understood, the AYA survivors might experience a sense of abandonment. By adopting a care ethics and narrative medicine approach we provide medical professionals a theoretical framework to better understand and care for AYA cancer survivors. Clinical trial number is 2012/1141.
Outcomes in patients with non‐invasive breast carcinoma
Authors: Kim Ryungsa , Kawai Ami , Wakisaka Megumi , Shimoyama Mika , Yasuda Naomi , Ito Mitsuya , Kin Takanori , Arihiro Koji 
Published: December 2022

AbstractBackground and AimNon‐invasive breast carcinoma is considered to be localized disease and is distinguished from invasive ductal and lobular carcinomas. The local recurrence of non‐invasive carcinoma after surgery may lead to development of invasive carcinoma and promote distant metastasis, which worsens the prognosis for breast cancer mortality. The distant metastasis of non‐invasive carcinoma may involve the ductal microvasculature without invasion. The outcomes of non‐invasive breast carcinoma were examined in this retrospective cohort study.Methods and ResultsOf 872 primary breast cancers diagnosed at a single center between May 2008 and March 2022, 93 (10.6%) were found to be non‐invasive carcinomas and were examined in this study. The breast cancer recurrence and survival rates of patients with non‐invasive carcinoma were analyzed retrospectively. The median follow‐up period was 1891 (range, 5–4804) days. All patients underwent surgical treatment [mastectomy with sentinel lymph node biopsy (SLNB) and partial mastectomy with or without SLNB, tumorectomy, and microdochectomy]. Postoperatively, radiation therapy was administered to 73 (78.4%) of the patients and endocrine therapy was administered to 64 (81.0%) of 79 patients with hormone‐receptor positivity. Of 26 patients who underwent partial mastectomy with SLNB, 24 (92.3%) showed isolated tumor cells in the SLNs on one‐step nucleic acid amplification. Local recurrence was observed in three (0.3%) patients; no distant metastasis was observed. One patient died of a noncancerous disease. The overall survival rate was 98.0% and the breast cancer‐specific survival rate was 100.0%.ConclusionsNon‐invasive breast carcinoma, like invasive breast carcinoma, causes local recurrence, but has a good prognosis without distant metastasis. The clinical significance of isolated tumor cells in the SLNs as a systemic component of non‐invasive breast carcinoma remains to be elucidated.
A Study to Evaluate Relative Bioavailability, Food Effect, and Pharmacodynamics of Tropifexor, a Farnesoid X Receptor Agonist, in Healthy Participants
Authors: Stringer Rowan , Chen Jin , Shah Bharti , Gu Jessie , Zhang Yiming , Prince William , Klickstein Lloyd B. , Woessner Ralph 
Published: December 2022

AbstractThis open‐label, randomized, 3‐treatment, 3‐period, 6‐sequence, crossover study in healthy subjects compared the pharmacokinetic and pharmacodynamic properties of a lipid‐based (soft gelatin capsule) prototype final market image (pFMI) formulation of tropifexor (90‐µg) to its clinical service form (CSF) and assessed the food effect for the pFMI formulation. In the fasted state, drug exposure was higher for the pFMI. The geometric mean ratios for pFMI versus CSF of peak concentration and area under the concentration–time curve were 2.0 and 1.5, respectively. No food effect was apparent for the pFMI formulation, and the geometric mean ratios for pFMI fed versus pFMI fasted of peak concentration and area under concentration–time curve were 1.0 and 1.0 respectively. Despite having lower systemic exposure, the CSF formulation provided a higher pharmacological response for the gut biomarker fibroblast growth factor 19. Under fasted conditions, fibroblast growth factor 19 maximum change from baseline serum concentration after drug administration and area under the change from baseline serum concentration–time curve from time 0 to 24 hours were 36% for CSF and 12% for FMI. For a second biomarker, serum 7‐alpha hydroxy‐4‐cholest‐3‐one, the pharmacological activity was comparable between CSF (fasted) and pFMI (both fasted and fed states). The pFMI offers advantages over the CSF in terms of insensitivity to food effect, lower intersubject variability, and overcoming solubility limitations.
Internet of Things‐based root disease classification in alfalfa plants using hybrid optimization‐enabled deep convolutional neural network
Authors: Jayapalan Daniel Francis Selvaraj , Ananth John Patrick 
Published: December 2022

SummaryIn this article, water cycle spider monkey optimization‐based deep convolutional neural network (WCSMO‐based deep CNN) is designed to classify root diseases in alfalfa plants. In the proposed method, the alfalfa plant root images are accessed remotely using a camera and transferred to the sink node to classify the disease. The proposed water cycle spider monkey optimization (WCSMO) algorithm performs the routing. Once the root images are received at base station or sink node, the images undergo preprocessing, segmentation, and classification. In the preprocessing module, a median filter is utilized to reduce the image noise. The preprocessed output is subjected to the segmentation phase, which is carried out using enhanced fuzzy C‐means clustering. The segmented results are passed to the classification step, where the deep convolutional neural network (deep CNN) is employed to categorize the root illness after being trained by the proposed WCSMO algorithm, which combines the water cycle algorithm and spider monkey optimization. The developed method achieved effective performance in terms of the metrics like sensitivity, accuracy, and specificity with the value of 0.9169, 0.9198, and 0.92. Moreover, the proposed WCSMO algorithm obtained the average energy and average throughput of 0.26641 J, and 91.483%, respectively.
Secured information sharing for supply chain management based on blockchain technology and optimal key generation process
Authors: Lahane Priti S. , Sharma Manish 
Published: December 2022

SummarySupply Chain Management (SCM) is one of the biggest important focal areas in most corporate environments. However, some difficulties are presented in the structure like high cost, privacy issues and distortions. Thus, new secured information sharing for SCM is proposed in this work and deals with the introduction of privacy preservation of data transfers among supply chains. Initially, a supply chain is constructed and the data transfer among the diverse levels takes place via blockchain technology. In the blockchain, security being a crucial factor, a new privacy preservation method is introduced. The initial information is converted to a sanitization procedure prior to transmission via blockchain technology, in which the information is turned into sanitized data. Similarly, the sanitized data is restored on the receiving end to obtain the original data. More importantly, key generation has a significant role in both processes, and it must be ideally chosen. The key is optimally chosen for this study using a new optimization algorithm called Fitness‐based Self‐adaptive Sea lion Optimization (FSA‐SLnO), which is a better variant of the conventional Sealion Optimization technique (SLnO). In terms of security, the proposed protected information sharing in SCM using block chain technology is evaluated by comparing it with traditional approaches.
Shuffled shepherd social optimization based deep learning for rice leaf disease classification and severity percentage prediction
Authors: Daniya Thavasilingam , Srinivasan Vigneshwari 
Published: December 2022

SummaryThe earlier diagnosis and classification of plant diseases has the ability to control the spread of illnesses on a variety of crops with the aim of improving crop quality and yield. The automatic system effectively recognizes the plant diseases at less error and cost without the interpretation of farm specialists. In this article, shuffled shepherd social optimization‐based deep learning (SSSO‐based deep learning) technique is developed to classify rice leaf disease and severity percentage prediction. The classification is carried out using deep maxout network and the severity percentage prediction is performed using deep LSTM. The training of both deep learning techniques is achieved using developed SSSO algorithm, which is the combination of shuffled shepherd optimization algorithm (SSOA) and social optimization algorithm. The proposed technique achieved maximum accuracy, sensitivity, specificity of 0.926, 0.935, 0.892, and minimum mean square error, and root mean square error of 0.106, and 0.326. The accuracy of the implemented approach is 7.24%, 5.29%, 4%, and 2.81% improved than the existing techniques, like bacterial leaf streak‐based UNet (BLSNet), multilayer maxout, resistance spot welding‐based deep recurrent neural network (RSW‐based deep RNN), and rider Henry gas solubility optimization_deep neuro fuzzy network (RHGSO_DNFN) + deep LSTM.
Fractional Artificial Bee Chicken Swarm Optimization technique for QoS aware virtual machine placement in cloud
Authors: Pushpa Ramaiah , Siddappa Maadappa 
Published: December 2022

SummaryCloud computing provides different constructive services in order to share huge scale information, computing resources, storage resources, and offer research knowledge. Cloud Service Providers (CSPs) afforded its services to cloud customers, usually in structure of Virtual Machines (VMs). In this paper, Fractional Artificial Bee Chicken Swarm Optimization (Fractional ABCSO) is introduced for VM placement in the cloud. The Fractional ABCSO is obtained by integrating the Fractional concept (FC), Chicken Swarm Optimization (CSO), and Artificial Bee Colony (ABC). Here, the cloud simulation is performed by means of VM and physical machine (PM). At first, VM placement is carried out using different system factors, such as Central Processing Unit (CPU), Million Instructions per Second (MIPS), bandwidth, migration cost, memory, frequency, power, along with Quality of Service (QoS). The developed Fractional ABCSO algorithm outperformed other existing techniques with regard to load, migration cost, and power consumption of 0.1614, 0.0535, and 0.0408.
Intelligent skin cancer diagnosis using adaptive k‐means segmentation and deep learning models
Authors: Enturi Bala Krishna Manash , Suhasini A. , Satyala Narayana 
Published: December 2022

SummarySince melanoma spreads swiftly throughout the body, it is typically a deadly form of skin cancer. Only when skin cancer is discovered early on is it usually treatable. In order to do this, this work proposes a unique melanoma detection model that has five main phases, including (i) pre‐processing, (ii) segmentation, (iii) feature extraction, (iv) suggested HKPCA based dimensionality reduction, and (v) classification. Pre‐processing is done first, and segmentation is done using a new adaptive k‐means methodology after that. After that, features from the gray‐level co‐occurrence matrix (GLCM), deviation relevance based local binary pattern (DRLBP), and gray‐level run‐length matrix (GLRM) is extracted. Extracted features were subjected for dimensionality reduction via hybrid kernel proposed principal component analysis (HKPCA). These dimension reduced features are then classified using deep belief network (DBN) framework, where the weights will be optimized by means of improved elephant herding optimization (IEHO). Finally, a comparison of the proposed and existing models' convergent performance is conducted.
Dynamics of Citrate Coordination on Gold Nanoparticles Under Low Specific Power Laser‐Induced Heating
Authors: Oliveira de Souza Danilo , Girardon Jean‐Sébastien , Hoffmann David J. , Berrier Elise 
Published: December 2022

AbstractSERS evolution recorded over a drop‐coated coffee‐ring pattern of citrate‐capped gold colloids was investigated as a function of time under low‐specific laser power. Spectral changes caused by plasmon‐induced reaction could not be detected, but a long‐term transient original spectral profile showing additional lines was observed. We performed deep qualitative and quantitative SERS intensity variation analysis based on the complementary use of extreme deviation and cross‐correlation statistics, which provided further insights on the behavior of citrate‐capping layers of gold nanoparticles upon laser illumination. More precisely, the cross‐correlation analysis made possible to follow the so‐called individual events denoting particular resonance structures, in which groups of modes were assigned to an evolution of citrate coordination on gold surface driven by photo‐activation. As a consequence, the detection limit was increased and new lines were related to the presence of a very low amount of dicarboxy‐acetone (DCA), which was already present in the system.
Metacognitive training for negative symptoms: Support for the cognitive model
Authors: Swanson Linda , Griffiths Helen , Moritz Steffen , Cervenka Simon 
Published: December 2022

AbstractDeveloping effective treatment options for negative symptoms of psychotic disorders remains a major unmet treatment need and area for further research. In a recent uncontrolled study by the main author, Metacognition Training (MCT) for negative symptoms was found to lead to fewer negative symptoms, less stigma and increased self‐rated reflective ability. As the analysis examined negative symptoms as a whole, we here performed an additional analysis on individual negative symptom items as recent research has suggested that negative symptoms are best conceptualized through a five‐factor model. It was found that the intervention led to changes specifically on sociality and blunted affect (with large effect sizes), which might reflect changes in both intrapersonal and interpersonal (meta)cognitive processes.
Amphiphilic Graphene Quantum Dots: Metal‐Free Photocatalyst for Hydrogen Evolution via Encapsulation of Organic Thermally Activated Delayed Fluorescence Photosensitizers
Authors: Park Hyunho , Serdiuk Illia E. , Park Soo Young 
Published: December 2022

AbstractDesigning a metal‐free photocatalyst for the photocatalytic hydrogen evolution reaction (HER) is a very important research goal. Although graphene quantum dots (GQDs) have already been demonstrated as HER photocatalysts, it is necessary to address the poor visible light absorption of GQDs to achieve higher efficiency in the hydrogen evolution reaction (HER) rate. We have synthesized amphiphilic GQD by hexylamine (HA) functionalization through an amide bond formation reaction. We confirmed that HA functionalized GQD (GQD‐HA) is amphiphilic and can act as the photocatalyst and templating surfactant at the same time. GQD‐HA can form much more stable composite nanoparticles with thermally activated delayed fluorescence (TADF) photosensitizers than bare GQD. Importantly, the HER performance and the stability of the composite systems are remarkably enhanced after HA functionalization. Through electrochemical analyses, it was verified that composite photosensitizer nanoparticles with GQD‐HA have efficient charge separation and fast charge transfer properties.