bluuebunny/crossref_metadata_2025_split huggingface dataset:
Assessing the risk of thromboembolism in cancer patients receiving immunotherapy
Authors: Goel Abhishek , Khorana Arjun , Kartika Thomas , Gowda Sonia , Tao Derrick L. , Thawani Rajat , Shatzel Joseph J. 
Published: December 2021

AbstractMalignancy has long been implicated with hypercoagulability, leading to an increased rate of both venous and arterial thromboembolic events (VTE and ATE). Immunotherapy has established itself as a cornerstone of modern cancer therapy by promoting antitumor immune responses, though there have been some suggestions that immune‐related adverse events could include increased rates of VTE and ATE. In this review, we examine the available evidence regarding the use of immune checkpoint inhibitors (ICIs) and thrombosis. First, we describe the potential mechanisms by which ICIs might lead to thrombophilia given the overlap between the immune system, coagulation cascade, and platelet adhesion and activation. In addition, while there are some preclinical data evaluating immunotherapy‐associated ATEs in animal models, there is a paucity of evidence exploring potential mechanism of VTEs in ICIs. Second, we review the incidence of ATE and VTE in patients receiving ICIs in the published literature. Finally, we discuss current limitations in understanding, areas of conflicting evidence, and approaches to further investigation.
Repetitive transcranial magnetic stimulation modulates cortical–subcortical connectivity in sensorimotor network
Authors: Chen Jing , Fan Yanzi , Wei Wei , Wang Luoyu , Wang Xiaoyu , Fan Fengmei , Jia Zejuan , Li Mengting , Wang Jinhui , Zou Qihong , Chen Bing , Lv Yating 
Published: December 2021

AbstractRepetitive transcranial magnetic stimulation (rTMS) holds the ability to modulate the connectivity within the stimulated network. However, whether and how the rTMS targeted over the primary motor cortex (M1) could affect the connectivity within the sensorimotor network (SMN) is not fully elucidated. Hence, in this study, we investigated the after‐effects of rTMS over left M1 at different frequencies on connectivity within SMN. Forty‐five healthy participants were recruited and randomly divided into three groups according to rTMS frequencies (high‐frequency [HF], 3 Hz; low‐frequency [LF], 1 Hz; and SHAM). Participants received 1‐Hz, 3‐Hz or sham stimulation and underwent two functional magnetic resonance imaging (fMRI) scanning sessions before and after rTMS intervention. Using resting‐state functional connectivity (FC) approach, we found that high‐ and low‐frequency rTMS had opposing effects on FC within the SMN, especially for connectivity with subcortical regions (i.e., putamen, thalamus and cerebellum). Specifically, the reductions in connectivity between cortical and subcortical regions within cortico‐basal ganglia thalamo‐cortical circuits and the cognitive loop of cerebellum, and increased connectivity between cortical and subdivisions within the sensorimotor loop of cerebellum were observed after high‐frequency rTMS intervention, whereas the thalamus and cognitive cerebellum subdivisions exhibited increased connectivity, and sensorimotor cerebellum subdivisions showed decreased connectivity with stimulated target after low‐frequency stimulation. Collectively, these findings demonstrated the alterations of connectivity within SMN after rTMS intervention at different frequencies and may help to understand the mechanisms of rTMS treatment for movement disorders associated with deficits in subcortical regions such as Parkinson's disease, Huntington's disease and Tourette's syndrome.
Balanced hierarchical max margin matrix factorization for recommendation system
Authors: Ravakhah Mahdi , Jalali Mehrdad , Forghani Yahya , Sheibani Reza 
Published: December 2021

AbstractMatrix factorization (MF) is one of the most important regression analysis methods used in recommendation systems. Max margin matrix factorization (MMMF) is a variant of MF which transforms the regression analysis problem into a single multi‐class classification problem, and then learns a multi‐class max margin classifier to achieve to a better error rate. One drawback of multi‐class MMMF is its bias towards class with small sample size. Therefore, hierarchical MMMF (HMF) which uses some two‐class MMMF problems in a hierarchical manner for multi‐class classification was proposed. Each two‐class MMMF of HMF is learned on the basis of thresholded training data which is too imbalanced for some two‐class MMMFs. Meanwhile, all training data is used in each two‐class MMMF. In the test phase of HMF, an imbalanced tree is used to estimate rating. Each node of this tree is a learned two‐class MMMF. In this paper, we propose a balanced HMF, which constructs a balanced tree with minimum depth. Each node of this tree is a learned two‐class MMMF on the basis of a part of data which is selected such that to be more balanced than that of the traditional HMF. Moreover, each part of data in our proposed balanced HMF does not have overlap with all previous parts of data. Therefore, the overall training data used in each step of balanced HMF is smaller than that of in the traditional HMF. Experimental results on real datasets show that training time, test time and error rate of our proposed balanced HMF is better than those of the traditional HMF.
RETRACTED: An efficient deep learning‐based video captioning framework using multi‐modal features
Authors: Varma Soumya , James Dinesh Peter 
Published: December 2021

AbstractVisual understanding has become more significant in gathering information in many real‐life applications. For a human, it is a trivial task to understand the content in a visual, however the same is a challenging task for a machine. Generating captions for images and videos for better understanding the situation is gaining more importance as they have wide application in assistive technologies, automatic video captioning, video summarizing, subtitling, blind navigation, and so on. The visual understanding framework will analyse the content present in the video to generate semantically accurate caption for the visual. Apart from the visual understanding of the situation, the gained semantics must be represented in a natural language like English, for which we require a language model. Hence, the semantics and grammar of the sentences being generated in English is yet another challenge. The captured description of the video is supposed to collect information of not just the objects contained in the scene, but it should also express how these objects are related to each other through the activity described in the scene, thus making the entire process a complex task for a machine. This work is an attempt to peep into the various methods for video captioning using deep learning methodologies, datasets that are widely used for these tasks and various evaluation metrics that are used for the performance comparison. The insights that we gained from our premiere work and the extensive literature review made us capable of proposing a practical, efficient video captioning architecture using deep learning which that will utilize the audio clues, external knowledge and attention context to improve the captioning process. Quantum deep learning architectures can bring about extraordinary results in object recognition tasks and feature extraction using convolutions.
Fisheries management on Lake Victoria at a crossroads: Assessing fishers’ perceptions on future management options in Uganda
Authors: Mpomwenda Veronica , Kristófersson Daði Mar , Taabu‐Munyaho Anthony , Tómasson Tumi , Pétursson Jón Geir 
Published: December 2021

AbstractFishers’ perceptions on the state of fisheries and the applicable fisheries management system in Lake Victoria (LV), Uganda, were assessed. Fisheries management in the lake is currently at a crossroads. The government abolished a co‐management system in November 2015 and installed the military to temporary enforce management. The objective of this study was to explore how fishers envisage future management options by assessing past management regimes and analysing perceptions of alternative regimes. A total of 273 semi‐structured interviews at six selected landing sites on LV in Uganda were conducted. Fishers targeted two dominant species, Nile perch, Lates niloticus (L.), mainly on motorised vessels representing the commercial fishers and dagaa, Rastrineobola argentea (Pellegrin), using both motorised and paddled vessels. The dominance of motorised fishing vessels depicted a consequence of the army operations and represents government priority to protect rather than regulate commercial fishing operations. Fishers mainly perceived regulations they knew about as effective, strongly opposed local governments as a management entity and assigned management to fisher groups as expected. The results support a management regime of key resource users organised by common interest groups to participate in decision‐making and combined government structures to regulate and enforce sustainable fisheries measures.
The varying use of online supplier portals in auto parts‐automotive value chains and its implications for learning and upgrading: The case for the Mexican and Turkish suppliers
Authors: Sancak Merve 
Published: December 2021

AbstractThis article examines the use of online supplier portals (OSPs) in managing lead firm–supplier relations in global auto parts‐automotive value chains (AACs) from suppliers’ point of view, and the implications of OSP usage for upgrading prospects of suppliers from middle‐income countries. The research is based on interviews with representatives of 33 auto parts suppliers and stakeholders of the auto parts‐automotive industry from Turkey and Mexico. The article has three main findings. Firstly, the use of OSPs is not the same across AACs and depends on the existing governance structures in these chains. Secondly, OSPs are used more in AACs with loose governance structures while their usage decreases as supplier–buyer coordination increases, which contrasts the mainstream expectations. Thirdly, the use of OSPs is not transforming the governance structures or implications of these structures for suppliers but rather reinforces the existing dynamics in these aspects.
Inhibition of phenolics on the in vitro digestion of noodles from the view of phenolics release
Authors: Wang Ruibin , Li Ming , Wu Gang , Hui Xiaodan , Tu Juncai , Brennan Margaret A. , Guo Boli , Brennan Charles S. 
Published: December 2021

AbstractThe inhibition mechanism of buckwheat phenolics on in vitro starch digestion was investigated using extruded noodles with buckwheat starch and phenolic extract (0.50%–2.00%). The cooking quality and reducing sugar released during in vitro digestion were studied, and the extractable phenolic content along digestion was also monitored to reveal a dose–effect relationship between reducing sugar released and the release of phenolics. Noodles containing increased phenolics released less reducing sugar (230–188 mg g−1) during digestion. Cooking and digestion made phenolics more extractable, and most of the phenolics were released at the end of the gastric phase (85.6%–94.8%) compared with during the small intestinal digestion. The IC50 of buckwheat phenolic extract (0.102 mg mL−1) was four times that of acarbose (0.032 mg mL−1). The inhibitory mechanism was further analysed using molecular docking, in which the activity of α‐amylase was inhibited by phenolics that bind with active sites of α‐amylase through hydrogen bonds and hydrophobic interaction. Phenolics interacting with starch and the released phenolics can both explain the reduction in starch digestion.
Phytochemicals and bioactivities of Goji (Lycium barbarum L. and Lycium chinense Mill.) leaves and their potential applications in the food industry: a review
Authors: Lei Zilun , Chen Xianqiang , Cao Fuliang , Guo Qirong , Wang Jiahong 
Published: December 2021

AbstractGoji leaves, including Lycium barbarum L. and Lycium chinense Mill. leaves, have been used as traditional Chinese medicine materials for nourishing kidneys and enhancing eyesight but are mostly discarded at present. The nutritional composition of Goji leaves is similar to that of Goji berries even some components are more plentiful in the former, such as flavonoids. This paper firstly reviews the main phytochemicals of Goji leaves. Also, updated information on the biological activities of Goji leaves is narrated. Based on the long use history and existing bioactivity data on Goji leaves, we propose their potential applications in the food industry and encourage further investigation on Goji leaves.
Detecting the presence of supernumerary teeth during the early mixed dentition stage using deep learning algorithms: A pilot study
Authors: Mine Yuichi , Iwamoto Yuko , Okazaki Shota , Nakamura Kentaro , Takeda Saori , Peng Tzu‐Yu , Mitsuhata Chieko , Kakimoto Naoya , Kozai Katsuyuki , Murayama Takeshi 
Published: December 2021

AbstractBackgroundSupernumerary teeth are a common anomaly and are frequently observed in paediatric patients. To prevent or minimize complications, early diagnosis and treatment is ideal in children with supernumerary teeth.AimThis study aimed to apply convolutional neural network (CNN)–based deep learning to detect the presence of supernumerary teeth in children during the early mixed dentition stage.DesignThree CNN models, AlexNet, VGG16‐TL, and InceptionV3‐TL, were employed in this study. A total of 220 panoramic radiographs (from children aged 6 years 0 months to 9 years 6 months) including supernumerary teeth (cases, n = 120) or no anomalies (controls, n = 100) were retrospectively analyzed. The CNN performances were assessed according to accuracy, sensitivity, specificity, receiver operating characteristic (ROC) curves, and area under the ROC curves for a cross‐validation test dataset.ResultsThe VGG16‐TL model had the highest performance according to accuracy, sensitivity, specificity, and area under the ROC curve, but the other models had similar performance.ConclusionCNN‐based deep learning is a promising approach for detecting the presence of supernumerary teeth during the early mixed dentition stage.
Effectiveness of technology‐based interventions on psychological morbidities, quality of life for informal caregivers of stroke survivors: A systematic review and meta‐analysis
Authors: Chin Wei Jien , Ho Yun Ling Selina , Ramazanu Sheena , Itoh Sakiko , Klainin‐Yobas Piyanee , Wu Xi Vivien 
Published: December 2021

AbstractAimsTo evaluate the effectiveness of technology‐based interventions in reducing psychological morbidities such as depressive symptomology, anxiety, burden and improving quality of life and self‐efficacy in informal caregivers of stroke survivors.DesignA systematic review and meta‐analysis.Data SourcesAn extensive search was systematically undertaken at CENTRAL, PubMed, Embase, Scopus, CINHAL, Web of Science and PsycInfo until January 2021. Grey literature and dissertations were searched in Google Scholar, ProQuest & Scholarbank@NUS. Studies involving registered trials were retrieved from Clinicaltrials.gov and CENTRAL, respectively.Review MethodsTwo reviewers independently screened the trials, conducted quality appraisal and extracted the data. Quality of the studies included in the review was assessed using Cochrane Risk of bias tool. Meta‐analysis was conducted using RevMan 5.4. Narrative synthesis was performed for studies where results could not be pooled statistically. The results were reported abiding Preferred Reporting Items for Systematic Reviews and Meta‐Analyses guidelines.ResultsThis review included 15 trials with a total of 1276 informal caregivers of stroke survivors. Eleven trials were included in the meta‐analysis. Subgroup analyses revealed that technology‐based interventions with structured educational programs were statistically significant in reducing depressive symptoms (d = −0.27, 95% CI [−0.49 to −0.05], p = .02). Technology‐based interventions with structured educational programs <3‐month revealed significant effects (d = −0.31, 95% CI [−0.49 to −0.13], p = .0009). Results of narrative synthesis reported technology‐based intervention with face‐to‐face training minimized depressive symptoms of informal caregivers. Notably, there were no statistically significant effects on anxiety, burden, quality of life and self‐efficacy outcomes.ConclusionTechnology‐based interventions had beneficial effects in alleviating depressive symptoms among informal caregivers.ImpactTechnology‐based interventions serve as a support mechanism for informal caregivers of stroke survivors who face time‐constrains. Further high‐quality randomized controlled trials are warranted to elucidate sustainability, optimal format and dosage of intervention.
Learning to eRead: A qualitative exploration of young children's developing eReader practices
Authors: Schmitt Kelly L. , Hurwitz Lisa B. , Nichols Deborah 
Published: December 2021

AbstractBackgroundPrevious eBook studies were primarily cross‐sectional surveys or experimental studies providing a snapshot of the impact of eBook reading on children's emergent literacy skills. Scholars have yet to characterize more fine grain developmental progressions in the use of eReaders and similar devices – that is, how children's eBook‐related practices evolve over time and what might be changing behaviourally over the course of repeated readings for any age group.ObjectivesThis is the first study to characterize young children's (2 to 3 years) use of eReaders over the span of several months under semi‐naturalistic conditions.MethodsTwenty five mothers and their 2.5‐ to 3.5‐year‐old child engaged in a series of documentation exercises and interviews around use of a novel eReader device. This study is exploratory and deductive in nature, and hypotheses were not set forth a priori.Results and ConclusionsThe results of the present study suggest that children develop increasing mastery of the affordances of eReaders as their device exposure increases. Over time, their ability to independently engage with devices rapidly increases. They transition from needing technical support from parents and high levels of encouragement to attend to literacy content over hotspots, to sometimes using the device independently, to considering the device a mainstay in their home – no longer a novelty.Implications for practice and/or policyThe developmental usability patterns noted in this study extend our naturalistic understanding of young children's dexterity with digital devices and point to methodological approaches that might yield more ecologically valid findings in future studies.
Quantitative evaluation of brain iron accumulation in different stages of Parkinson's disease
Authors: Li Kailyn R. , Avecillas‐Chasin Josue , Nguyen Thanh D. , Gillen Kelly M. , Dimov Alexey , Chang Eileen , Skudin Carly , Kopell Brian H. , Wang Yi , Shtilbans Alexander 
Published: December 2021

AbstractBackground and PurposeExcessive brain iron deposition is involved in Parkinson's disease (PD) pathogenesis. However, the correlation of iron accumulation in various brain nuclei is not well‐established in different stages of the disease. This cross‐sectional study aims to evaluate quantitative susceptibility mapping (QSM) as an imaging technique to measure brain iron accumulation in PD patients in different stages compared to healthy controls.MethodsNinety‐six PD patients grouped by their Hoehn and Yahr (H&Y) stages and 31 healthy controls were included in this analysis. The magnetic susceptibility values of the substantia nigra (SN), red nucleus (RN), caudate, putamen, and globus pallidus were obtained and compared.ResultsIron level was increased in the SN of PD patients in all stages versus controls (p < .001), with no significant difference within stages. Iron in the RN was significantly increased in stage II versus controls (p = .013) and combined stages III and IV versus controls (p < .001). The iron levels in caudate, putamen, and globus pallidus were not different between any groups.ConclusionsOur data suggest iron accumulation occurs early in the disease course and only in the SN and RN of these patients. This is a large cross‐sectional study of brain iron deposition in PD patients according to H&Y staging. Prospective studies are warranted to further validate QSM as a method to follow brain iron, which could serve as a disease biomarker and a therapeutic target.
Patent policy and economic growth: A survey
Authors: Chu Angus C. 
Published: December 2021

AbstractThis survey provides a selective review of the literature on patent policy, innovation and economic growth. The patent system is a useful policy tool for stimulating innovation given its importance on technological progress and economic growth. However, the patent system is a multidimensional system, which features multiple patent policy instruments. In this survey, we review some of the commonly discussed patent policy instruments, such as patent length, patent breadth and blocking patents, and also use a canonical Schumpeterian growth model to demonstrate their different effects on innovation and the macroeconomy.
Seasonal variation in maternal dietary diversity is reduced by small‐scale irrigation practices: A longitudinal study
Authors: Baye Kaleab , Mekonnen Dawit , Choufani Jowel , Yimam Seid , Bryan Elizabeth , Griffiths Jeffrey K. , Ringler Claudia 
Published: December 2021

AbstractSome agricultural practices, such as irrigation, have the potential to buffer seasonal dietary gaps and through increased production and consumption improve diets, particularly of the rural poor relying on subsistence farming but also for rural and urban households purchasing irrigated produce on local markets. The study aimed to evaluate the effect of seasonality and irrigation on women's diet in rural Ethiopia. Using a longitudinal study design, three rounds of surveys were conducted among women of reproductive age (15–49 years). Data on socioeconomic status, food consumption and haemoglobin concentration was collected. Energy and nutrient intakes were estimated using an interviewer‐administered multiple‐pass 24‐h recall. Women's dietary diversity score (WDDS), the proportion of women meeting the minimum dietary diversity for women (MDDW), haemoglobin concentration, the prevalence of anaemia and energy and nutrients intakes were compared between irrigators and nonirrigators and by season. Associations between MDDW/WDDS and irrigation status were assessed using fixed‐effect models, after adjusting for covariates. WDDS was low (3–4 out of 10 food groups) and exhibited high seasonal variability (p < 0.05). Diets were predominantly cereal‐based, with little consumption of nutrient‐dense foods like fruits and animal source foods. High seasonal variability in energy, protein, vitamin C, calcium, iron and zinc intakes were observed (p < 0.01). Irrigators were more likely to meet the MDDW than women from non‐irrigating households (p < 0.05). No cases of malaria were reported from the three rounds of screening. There is a high seasonal variation in women's diet, but this could be partly offset by irrigation practices.