15,319 research outputs found

    Towards Autonomous Selective Harvesting: A Review of Robot Perception, Robot Design, Motion Planning and Control

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    This paper provides an overview of the current state-of-the-art in selective harvesting robots (SHRs) and their potential for addressing the challenges of global food production. SHRs have the potential to increase productivity, reduce labour costs, and minimise food waste by selectively harvesting only ripe fruits and vegetables. The paper discusses the main components of SHRs, including perception, grasping, cutting, motion planning, and control. It also highlights the challenges in developing SHR technologies, particularly in the areas of robot design, motion planning and control. The paper also discusses the potential benefits of integrating AI and soft robots and data-driven methods to enhance the performance and robustness of SHR systems. Finally, the paper identifies several open research questions in the field and highlights the need for further research and development efforts to advance SHR technologies to meet the challenges of global food production. Overall, this paper provides a starting point for researchers and practitioners interested in developing SHRs and highlights the need for more research in this field.Comment: Preprint: to be appeared in Journal of Field Robotic

    Likelihood Asymptotics in Nonregular Settings: A Review with Emphasis on the Likelihood Ratio

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    This paper reviews the most common situations where one or more regularity conditions which underlie classical likelihood-based parametric inference fail. We identify three main classes of problems: boundary problems, indeterminate parameter problems -- which include non-identifiable parameters and singular information matrices -- and change-point problems. The review focuses on the large-sample properties of the likelihood ratio statistic. We emphasize analytical solutions and acknowledge software implementations where available. We furthermore give summary insight about the possible tools to derivate the key results. Other approaches to hypothesis testing and connections to estimation are listed in the annotated bibliography of the Supplementary Material

    Neural Architecture Search: Insights from 1000 Papers

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    In the past decade, advances in deep learning have resulted in breakthroughs in a variety of areas, including computer vision, natural language understanding, speech recognition, and reinforcement learning. Specialized, high-performing neural architectures are crucial to the success of deep learning in these areas. Neural architecture search (NAS), the process of automating the design of neural architectures for a given task, is an inevitable next step in automating machine learning and has already outpaced the best human-designed architectures on many tasks. In the past few years, research in NAS has been progressing rapidly, with over 1000 papers released since 2020 (Deng and Lindauer, 2021). In this survey, we provide an organized and comprehensive guide to neural architecture search. We give a taxonomy of search spaces, algorithms, and speedup techniques, and we discuss resources such as benchmarks, best practices, other surveys, and open-source libraries

    Examples of works to practice staccato technique in clarinet instrument

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    Klarnetin staccato tekniğini güçlendirme aşamaları eser çalışmalarıyla uygulanmıştır. Staccato geçişlerini hızlandıracak ritim ve nüans çalışmalarına yer verilmiştir. Çalışmanın en önemli amacı sadece staccato çalışması değil parmak-dilin eş zamanlı uyumunun hassasiyeti üzerinde de durulmasıdır. Staccato çalışmalarını daha verimli hale getirmek için eser çalışmasının içinde etüt çalışmasına da yer verilmiştir. Çalışmaların üzerinde titizlikle durulması staccato çalışmasının ilham verici etkisi ile müzikal kimliğe yeni bir boyut kazandırmıştır. Sekiz özgün eser çalışmasının her aşaması anlatılmıştır. Her aşamanın bir sonraki performans ve tekniği güçlendirmesi esas alınmıştır. Bu çalışmada staccato tekniğinin hangi alanlarda kullanıldığı, nasıl sonuçlar elde edildiği bilgisine yer verilmiştir. Notaların parmak ve dil uyumu ile nasıl şekilleneceği ve nasıl bir çalışma disiplini içinde gerçekleşeceği planlanmıştır. Kamış-nota-diyafram-parmak-dil-nüans ve disiplin kavramlarının staccato tekniğinde ayrılmaz bir bütün olduğu saptanmıştır. Araştırmada literatür taraması yapılarak staccato ile ilgili çalışmalar taranmıştır. Tarama sonucunda klarnet tekniğin de kullanılan staccato eser çalışmasının az olduğu tespit edilmiştir. Metot taramasında da etüt çalışmasının daha çok olduğu saptanmıştır. Böylelikle klarnetin staccato tekniğini hızlandırma ve güçlendirme çalışmaları sunulmuştur. Staccato etüt çalışmaları yapılırken, araya eser çalışmasının girmesi beyni rahatlattığı ve istekliliği daha arttırdığı gözlemlenmiştir. Staccato çalışmasını yaparken doğru bir kamış seçimi üzerinde de durulmuştur. Staccato tekniğini doğru çalışmak için doğru bir kamışın dil hızını arttırdığı saptanmıştır. Doğru bir kamış seçimi kamıştan rahat ses çıkmasına bağlıdır. Kamış, dil atma gücünü vermiyorsa daha doğru bir kamış seçiminin yapılması gerekliliği vurgulanmıştır. Staccato çalışmalarında baştan sona bir eseri yorumlamak zor olabilir. Bu açıdan çalışma, verilen müzikal nüanslara uymanın, dil atış performansını rahatlattığını ortaya koymuştur. Gelecek nesillere edinilen bilgi ve birikimlerin aktarılması ve geliştirici olması teşvik edilmiştir. Çıkacak eserlerin nasıl çözüleceği, staccato tekniğinin nasıl üstesinden gelinebileceği anlatılmıştır. Staccato tekniğinin daha kısa sürede çözüme kavuşturulması amaç edinilmiştir. Parmakların yerlerini öğrettiğimiz kadar belleğimize de çalışmaların kaydedilmesi önemlidir. Gösterilen azmin ve sabrın sonucu olarak ortaya çıkan yapıt başarıyı daha da yukarı seviyelere çıkaracaktır

    A pilot investigation of differential hydroxymethylation levels in patient-derived neural stem cells implicates altered cortical development in bipolar disorder

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    IntroductionBipolar disorder (BD) is a chronic mental illness characterized by recurrent episodes of mania and depression and associated with social and cognitive disturbances. Environmental factors, such as maternal smoking and childhood trauma, are believed to modulate risk genotypes and contribute to the pathogenesis of BD, suggesting a key role in epigenetic regulation during neurodevelopment. 5-hydroxymethylcytosine (5hmC) is an epigenetic variant of particular interest, as it is highly expressed in the brain and is implicated in neurodevelopment, and psychiatric and neurological disorders.MethodsInduced pluripotent stem cells (iPSCs) were generated from the white blood cells of two adolescent patients with bipolar disorder and their same-sex age-matched unaffected siblings (n = 4). Further, iPSCs were differentiated into neuronal stem cells (NSCs) and characterized for purity using immuno-fluorescence. We used reduced representation hydroxymethylation profiling (RRHP) to perform genome-wide 5hmC profiling of iPSCs and NSCs, to model 5hmC changes during neuronal differentiation and assess their impact on BD risk. Functional annotation and enrichment testing of genes harboring differentiated 5hmC loci were performed with the online tool DAVID.ResultsApproximately 2 million sites were mapped and quantified, with the majority (68.8%) located in genic regions, with elevated 5hmC levels per site observed for 3’ UTRs, exons, and 2-kb shorelines of CpG islands. Paired t-tests of normalized 5hmC counts between iPSC and NSC cell lines revealed global hypo-hydroxymethylation in NSCs and enrichment of differentially hydroxymethylated sites within genes associated with plasma membrane (FDR = 9.1 × 10−12) and axon guidance (FDR = 2.1 × 10−6), among other neuronal processes. The most significant difference was observed for a transcription factor binding site for the KCNK9 gene (p = 8.8 × 10−6), encoding a potassium channel protein involved in neuronal activity and migration. Protein–protein-interaction (PPI) networking showed significant connectivity (p = 3.2 × 10−10) between proteins encoded by genes harboring highly differentiated 5hmC sites, with genes involved in axon guidance and ion transmembrane transport forming distinct sub-clusters. Comparison of NSCs of BD cases and unaffected siblings revealed additional patterns of differentiation in hydroxymethylation levels, including sites in genes with functions related to synapse formation and regulation, such as CUX2 (p = 2.4 × 10−5) and DOK-7 (p = 3.6 × 10−3), as well as an enrichment of genes involved in the extracellular matrix (FDR = 1.0 × 10−8).DiscussionTogether, these preliminary results lend evidence toward a potential role for 5hmC in both early neuronal differentiation and BD risk, with validation and more comprehensive characterization to be achieved through follow-up study

    Receptor–ligand pair typing and prognostic risk model of response or resistance to immune checkpoint inhibitors in lung adenocarcinoma

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    IntroductionCurrently, programmed cell death-1 (PD-1)-targeted treatment is ineffective for a sizable minority of patients, and drug resistance still cannot be overcome.MethodsTo explore the mechanisms of immunotherapy and identify new therapeutic opportunities in lung adenocarcinoma (LUAD), data from patients who did and did not respond to the anti-PD-1 treatment were evaluated using single-cell RNA sequencing, and bulk RNA sequencing were collected.ResultsWe investigated the gene expression that respond or not respond to immunotherapy in diverse cell types and revealed transcriptional characteristics at the single-cell level. To ultimately explore the molecular response or resistance to anti-PD-1 therapy, cell-cell interactions were carried out to identify the different LRIs (ligand-receptor interactions) between untreated patients vs. no-responders, untreated patients vs. responders, and responders vs. non-responders. Next, two molecular subgroups were proposed based on 73 LRI genes, and subtype 1 had a poor survival status and was likely to be the immunosuppressive tumor subtype. Furthermore, based on the LASSO Cox regression analysis results, we found that TNFSF13, AXL, KLRK1, FAS, PROS1, and CDH1 can be distinct prognostic biomarkers, immune infiltration levels, and responses to immunotherapy in LUAD.DiscussionAltogether, the effects of immunotherapy were connected to LRIs scores, indicating that potential medications targeting these LRIs could contribute to the clinical benefit of immunotherapy. Our integrative omics analysis revealed the mechanisms underlying the anti-PD-1 therapy response and offered abundant clues for potential strategies to improve precise diagnosis and immunotherapy

    Machine Learning Research Trends in Africa: A 30 Years Overview with Bibliometric Analysis Review

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    In this paper, a critical bibliometric analysis study is conducted, coupled with an extensive literature survey on recent developments and associated applications in machine learning research with a perspective on Africa. The presented bibliometric analysis study consists of 2761 machine learning-related documents, of which 98% were articles with at least 482 citations published in 903 journals during the past 30 years. Furthermore, the collated documents were retrieved from the Science Citation Index EXPANDED, comprising research publications from 54 African countries between 1993 and 2021. The bibliometric study shows the visualization of the current landscape and future trends in machine learning research and its application to facilitate future collaborative research and knowledge exchange among authors from different research institutions scattered across the African continent

    OLIG2 neural progenitor cell development and fate in Down syndrome

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    Down syndrome (DS) is caused by triplication of human chromosome 21 (HSA21) and is the most common genetic form of intellectual disability. It is unknown precisely how triplication of HSA21 results in the intellectual disability, but it is thought that the global transcriptional dysregulation caused by trisomy 21 perturbs multiple aspects of neurodevelopment that cumulatively contribute to its etiology. While the characteristics associated with DS can arise from any of the genes triplicated on HSA21, in this work we focus on oligodendrocyte transcription factor 2 (OLIG2). The progeny of neural progenitor cells (NPCs) expressing OLIG2 are likely to be involved in many of the cellular changes underlying the intellectual disability in DS. To explore the fate of OLIG2+ neural progenitors, we took advantage of two distinct models of DS, the Ts65Dn mouse model and induced pluripotent stem cells (iPSCs) derived from individuals with DS. Our results from these two systems identified multiple perturbations in development in the cellular progeny of OLIG2+ NPCs. In Ts65Dn, we identified alterations in neurons and glia derived from the OLIG2 expressing progenitor domain in the ventral spinal cord. There were significant differences in the number of motor neurons and interneurons present in the trisomic lumbar spinal cord depending on age of the animal pointing both to a neurodevelopment and a neurodegeneration phenotype in the Ts65Dn mice. Of particular note, we identified changes in oligodendrocyte (OL) maturation in the trisomic mice that are dependent on spatial location and developmental origin. In the dorsal corticospinal tract, there were significantly fewer mature OLs in the trisomic mice, and in the lateral funiculus we observed the opposite phenotype with more mature OLs being present in the trisomic animals. We then transitioned our studies into iPSCs where we were able to pattern OLIG2+ NPCs to either a spinal cord-like or a brain-like identity and study the OL lineage that differentiated from each progenitor pool. Similar to the region-specific dysregulation found in the Ts65Dn spinal cord, we identified perturbations in trisomic OLs that were dependent on whether the NPCs had been patterned to a brain-like or spinal cord-like fate. In the spinal cord-like NPCs, there was no difference in the proportion of cells expressing either OLIG2 or NKX2.2, the two transcription factors whose co-expression is essential for OL differentiation. Conversely, in the brain-like NPCs, there was a significant increase in OLIG2+ cells in the trisomic culture and a decrease in NKX2.2 mRNA expression. We identified a sonic hedgehog (SHH) signaling based mechanism underlying these changes in OLIG2 and NKX2.2 expression in the brain-like NPCs and normalized the proportion of trisomic cells expressing the transcription factors to euploid levels by modulating the activity of the SHH pathway. Finally, we continued the differentiation of the brain-like and spinal cord-like NPCs to committed OL precursor cells (OPCs) and allowed them to mature. We identified an increase in OPC production in the spinal cord-like trisomic culture which was not present in the brain-like OPCs. Conversely, we identified a maturation deficit in the brain-like trisomic OLs that was not present in the spinal cord-like OPCs. These results underscore the importance of regional patterning in characterizing changes in cell differentiation and fate in DS. Together, the findings presented in this work contribute to the understanding of the cellular and molecular etiology of the intellectual disability in DS and in particular the contribution of cells differentiated from OLIG2+ progenitors

    Transfer learning for operator selection: A reinforcement learning approach

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    In the past two decades, metaheuristic optimisation algorithms (MOAs) have been increasingly popular, particularly in logistic, science, and engineering problems. The fundamental characteristics of such algorithms are that they are dependent on a parameter or a strategy. Some online and offline strategies are employed in order to obtain optimal configurations of the algorithms. Adaptive operator selection is one of them, and it determines whether or not to update a strategy from the strategy pool during the search process. In the field of machine learning, Reinforcement Learning (RL) refers to goal-oriented algorithms, which learn from the environment how to achieve a goal. On MOAs, reinforcement learning has been utilised to control the operator selection process. However, existing research fails to show that learned information may be transferred from one problem-solving procedure to another. The primary goal of the proposed research is to determine the impact of transfer learning on RL and MOAs. As a test problem, a set union knapsack problem with 30 separate benchmark problem instances is used. The results are statistically compared in depth. The learning process, according to the findings, improved the convergence speed while significantly reducing the CPU time
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