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"Yang, M"
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An IoT platform for smart metal forming
Manufacturers in the metal forming industry are paying attention on smart manufacturing with the industrial internet of things (IIoT). An innovation has been occurring by changing metal forming processes from analog to digital by utilizing servo press machine and IT technology for improving efficiency and worth of the mass production manufacturing technology and of ability for the SDGs. This paper aims to introduce initiatives to survey of the current situation and formulation of strategies on the digital transformation in metal forming promoted by the Sokeizai Centre in Japan. An IoT platform for smart metal forming which has been developed based on the strategies is also introduced. The platform consists of sensor system for visualization of forming processes, sensor data wireless communication using local 5G and data assimilation with process simulation. Several sensing systems developed for process visualization are introduced.
Journal Article
Feminist art activisms and artivisms
The first volume in the new Plural series, this publication seeks to critically dissect the term 'activism,' which today seems to have become a catchword for any woman's empowerment through the arts, and reveal the diversity of practices and realities that it comprises. Presenting a range of critical insights, perspectives, and practices from artists, activists, and academics, it reflects on the role of feminist interventions in the field of contemporary art, the public sphere, and politics. In the process, it touches upon broader questions of cultural difference, history, class, economic standing, ecological issues, and sexual orientation, as well as the ways in which these intersect.
Book
The Detection of Motor Bearing Fault with Maximal Overlap Discrete Wavelet Packet Transform and Teager Energy Adaptive Spectral Kurtosis
Motor bearings are one of the most critical components in rotating machinery. Envelope demodulation analysis has been widely used to demodulate bearing vibration signals to extract bearing defect frequency components but one of the main challenges is to accurately locate the major fault-induced frequency band with a high signal-to-noise ratio (SNR) for demodulation. Hence, an enhanced fault detection method combining the maximal overlap discrete wavelet packet transform (MODWPT) and the Teager energy adaptive spectral kurtosis (TEASK) denoising algorithms is proposed for identifying the weak periodic impulses. The Teager energy power spectrum (TEPS) defines the sparse representation of the filtered signals of the MODWPT in the frequency domain via the Teager energy operator (TEO); the TEASK helps determine the most informative frequency band for demodulation. The methodology is compared in terms of performance with the fast Kurtogram and the Autogram methods. The simulation and practical application examples have shown that the proposed MODWPT-TEASK method outperforms the above two methods in diagnosing defects of motor bearings.
Journal Article
Neuropsychiatric symptoms and imbalance of atrophy in behavioral variant frontotemporal dementia
Behavioral variant frontotemporal dementia is characterized by heterogeneous frontal, insular, and anterior temporal atrophy patterns that vary along left–right and dorso‐ventral axes. Little is known about how these structural imbalances impact clinical symptomatology. The goal of this study was to assess the frequency of frontotemporal asymmetry (right‐ or left‐lateralization) and dorsality (ventral or dorsal predominance of atrophy) and to investigate their clinical correlates. Neuropsychiatric symptoms and structural images were analyzed for 250 patients with behavioral variant frontotemporal dementia. Frontotemporal atrophy was most often symmetric while left‐lateralized (9%) and right‐lateralized (17%) atrophy were present in a minority of patients. Atrophy was more often ventral (32%) than dorsal (3%) predominant. Patients with right‐lateralized atrophy were characterized by higher severity of abnormal eating behavior and hallucinations compared to those with left‐lateralized atrophy. Subsequent analyses clarified that eating behavior was associated with right atrophy to a greater extent than a lack of left atrophy, and hallucinations were driven mainly by right atrophy. Dorsality analyses showed that anxiety, euphoria, and disinhibition correlated with ventral‐predominant atrophy. Agitation, irritability, and depression showed greater severity with a lack of regional atrophy, including in dorsal regions. Aberrant motor behavior and apathy were not explained by asymmetry or dorsality. This study provides additional insight into how anatomical heterogeneity influences the clinical presentation of patients with behavioral variant frontotemporal dementia. Behavioral symptoms can be associated not only with the presence or absence of focal atrophy, but also with right/left or dorsal/ventral imbalance of gray matter volume.
Journal Article
Pressure-induced monotonic enhancement of Tc to over 30 K in superconducting Pr0.82Sr0.18NiO2 thin films
The successful synthesis of superconducting infinite-layer nickelate thin films with the highest
T
c
≈ 15 K has ignited great enthusiasm for this material class as potential analogs of the high-
T
c
cuprates. Pursuing a higher
T
c
is always an imperative task in studying a new superconducting material system. Here we report high-quality Pr
0.82
Sr
0.18
NiO
2
thin films with
T
c
onset
≈ 17 K synthesized by carefully tuning the amount of CaH
2
in the topotactic chemical reduction and the effect of pressure on its superconducting properties by measuring electrical resistivity under various pressures in a cubic anvil cell apparatus. We find that the onset temperature of the superconductivity,
T
c
onset
, can be enhanced monotonically from ~17 K at ambient pressure to ~31 K at 12.1 GPa without showing signatures of saturation upon increasing pressure. This encouraging result indicates that the
T
c
of infinite-layer nickelates superconductors still has room to go higher and it can be further boosted by applying higher pressures or strain engineering in the heterostructure films.
Despite much recent effort, the highest reported
T
c
of the infinite-layer nickelates remains lower than 15 K. Here, the authors apply pressure to Pr
0.82
Sr
0.18
NiO
2
thin films and observe a monotonic increase of
T
c
to 31 K at 12.1 GPa, an increase that does not level off with increasing pressure.
Journal Article
GWAS meta-analysis reveals novel loci and genetic correlates for general cognitive function: a report from the COGENT consortium
The complex nature of human cognition has resulted in cognitive genomics lagging behind many other fields in terms of gene discovery using genome-wide association study (GWAS) methods. In an attempt to overcome these barriers, the current study utilized GWAS meta-analysis to examine the association of common genetic variation (~8M single-nucleotide polymorphisms (SNP) with minor allele frequency ⩾1%) to general cognitive function in a sample of 35 298 healthy individuals of European ancestry across 24 cohorts in the Cognitive Genomics Consortium (COGENT). In addition, we utilized individual SNP lookups and polygenic score analyses to identify genetic overlap with other relevant neurobehavioral phenotypes. Our primary GWAS meta-analysis identified two novel SNP loci (top SNPs: rs76114856 in the
CENPO
gene on chromosome 2 and rs6669072 near
LOC105378853
on chromosome 1) associated with cognitive performance at the genome-wide significance level (
P
<5 × 10
−8
). Gene-based analysis identified an additional three Bonferroni-corrected significant loci at chromosomes 17q21.31, 17p13.1 and 1p13.3. Altogether, common variation across the genome resulted in a conservatively estimated SNP heritability of 21.5% (s.e.=0.01%) for general cognitive function. Integration with prior GWAS of cognitive performance and educational attainment yielded several additional significant loci. Finally, we found robust polygenic correlations between cognitive performance and educational attainment, several psychiatric disorders, birth length/weight and smoking behavior, as well as a novel genetic association to the personality trait of openness. These data provide new insight into the genetics of neurocognitive function with relevance to understanding the pathophysiology of neuropsychiatric illness.
Journal Article
Systematic Review and Meta-Analysis of the Association Between Sarcopenia and Dysphagia
Sarcopenia, an age-related decrease in muscle mass and function, is associated with several potential adverse health outcomes. Its association with another age-related syndrome, dysphagia remains unclear. This systematic review and meta-analysis aims to explore the association between sarcopenia and dysphagia.
PubMed, Embase, Scopus and CINAHL were searched for cross-sectional, case-control and cohort studies that investigated the association between sarcopenia and dysphagia. First author, publication year, study type, sample size, inclusion and exclusion criteria, participant demographics, definition and measurement for evaluation of sarcopenia and dysphagia, main outcomes were retrieved. The association between sarcopenia and dysphagia were expressed by odds ratio (OR) and 95% confidence interval (CI).
9 studies are eligible in the systematic review, and 5 cross-sectional studies comprising 913 participants which showed dichotomous classification of sarcopenia and dysphagia were included in the meta-analysis. The crude odds ratios (ORs) were extracted from 5 studies, and 4 of them also provide adjusted ORs. The crude ORs between sarcopenia and dysphagia is 6.17 (95% CI, 3.81-10.00), after adjusting for some confounders, such as age, sex, Barthel Index score, nutritional status, sarcopenia is also have an association with dysphagia (adjusted ORs, 4.06; 95% CI, 2.27-7.29). The subgroup analysis showed that there was no significant difference between different sarcopenia diagnostic criteria, assessment tools of skeletal muscle mass and dysphagia.
Sarcopenia was positively associated with dysphagia. Prevention and screening of dysphagia is essential among sarcopenic old patients. The causal relationship requires more prospective cohort study for confirmation.
Journal Article
A Relational Formulation of Quantum Mechanics
Non-relativistic quantum mechanics is reformulated here based on the idea that relational properties among quantum systems, instead of the independent properties of a quantum system, are the most fundamental elements to construct quantum mechanics. This idea, combining with the emphasis that measurement of a quantum system is a bidirectional interaction process, leads to a new framework to calculate the probability of an outcome when measuring a quantum system. In this framework, the most basic variable is the relational probability amplitude. Probability is calculated as summation of weights from the alternative measurement configurations. The properties of quantum systems, such as superposition and entanglement, are manifested through the rules of counting the alternatives. Wave function and reduced density matrix are derived from the relational probability amplitude matrix. They are found to be secondary mathematical tools that equivalently describe a quantum system without explicitly calling out the reference system. Schrödinger Equation is obtained when there is no entanglement in the relational probability amplitude matrix. Feynman Path Integral is used to calculate the relational probability amplitude, and is further generalized to formulate the reduced density matrix. In essence, quantum mechanics is reformulated as a theory that describes physical systems in terms of relational properties.
Journal Article
Artificial Intelligence in Lung Cancer Pathology Image Analysis
Objective: Accurate diagnosis and prognosis are essential in lung cancer treatment selection and planning. With the rapid advance of medical imaging technology, whole slide imaging (WSI) in pathology is becoming a routine clinical procedure. An interplay of needs and challenges exists for computer-aided diagnosis based on accurate and efficient analysis of pathology images. Recently, artificial intelligence, especially deep learning, has shown great potential in pathology image analysis tasks such as tumor region identification, prognosis prediction, tumor microenvironment characterization, and metastasis detection. Materials and Methods: In this review, we aim to provide an overview of current and potential applications for AI methods in pathology image analysis, with an emphasis on lung cancer. Results: We outlined the current challenges and opportunities in lung cancer pathology image analysis, discussed the recent deep learning developments that could potentially impact digital pathology in lung cancer, and summarized the existing applications of deep learning algorithms in lung cancer diagnosis and prognosis. Discussion and Conclusion: With the advance of technology, digital pathology could have great potential impacts in lung cancer patient care. We point out some promising future directions for lung cancer pathology image analysis, including multi-task learning, transfer learning, and model interpretation.
Journal Article