Gastric adenocarcinoma with enteroblastic differentiation (GAED) is rare and its clinicopathological characteristics are not well documented. However, reports indicate that it exhibits more ...aggressive characteristics, including lymph node metastasis or liver metastasis, than a conventional gastric adenocarcinoma. Herein, we report a case of GAED with rapid recurrence and disease progression. A 55-year-old male, diagnosed with gastric cancer (GC), demonstrated initial endoscopic findings suggestive of advanced GC. He underwent curative resection since there was no evidence of lymph node or distant metastases. The disease was reported as an early GC that was confined to the submucosal layer, without evidence of lymph node metastasis in the final pathological results. However, six months after surgery, multiple hepatic metastases were found during abdominal computed tomography; the pathological results were consistent with metastasis from the GC. Immunohistochemistry of the primary carcinoma pathological specimens showed positive results for alpha-fetoprotein and sal-like protein 4, suggesting enteroblastic differentiation, which is thought to be associated with rapid recurrence and disease progression.
This paper presents an internet of things (IoTs) enabled smart meter with energy-efficient simultaneous wireless information and power transfer (SWIPT) for the wireless powered smart grid ...communication network. The SWIPT technique with energy harvesting (EH) is an attractive solution for prolonging the battery life of ultra-low power devices. The motivation for energy efficiency (EE) maximization is to increase the efficient use of energy and improve the battery life of the IoT devices embedded in smart meter. In the system model, the smart meter is equipped with an IoT device, which implements the SWIPT technique in power splitting (PS) mode. This paper aims at the EE maximization and considers the orthogonal frequency division multiplexing distributed antenna system (OFDM-DAS) for the smart meters in the downlink with IoT enabled PS-SWIPT system. The EE maximization is a nonlinear and non-convex optimization problem. We propose an optimal power allocation algorithm for the non-convex EE maximization problem by the Lagrange method and proportional fairness to optimal power allocation among smart meters. The proposed algorithm shows a clear advantage, where total power consumption is considered in the EE maximization with energy constraints. Furthermore, EE vs. spectral efficiency (SE) tradeoff is investigated. The results of our algorithm reveal that EE improves with EH requirements.
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IZUM, KILJ, NUK, PILJ, PNG, SAZU, UL, UM, UPUK
Lead halide perovskites (LHPs) are emerging as promising materials for light-emitting device applications because of the tunability of the band gap, narrow emission, solution processability, and ...flexibility. Typically, LHP nanocrystals (NCs) with surface ligands show high photoluminescence quantum yields because of charge-carrier confinement with higher exciton binding energy (E b). However, the conventionally used oleylamine (OAm) ligands result in the low electrical conductivity and stability of perovskite NCs (PNCs) because of a long carbon chain without conjugation bonds and weak interaction with the surface of NCs. Here, we report the effect of bulkiness and chain length of ligand materials on the properties and stability of CsPbBr3 PNCs by replacing OAm with other suitable ligands. The effect of the bulkiness of quaternary ammonium bromide (QAB) ligands was systemically studied. The less bulky QAB ligands surrounded the surface of NCs effectively, and brought better surface passivation and less aggregation compared to bulky QAB ligands, and finally the optical property and stability of CsPbBr3 PNCs were enhanced. Furthermore, the electrical property of CsPbBr3 PNCs was optimized by tuning the long-chain length of QAB ligands for balanced charge-carrier transport. Finally, we achieved highly efficient green emissive CsPbBr3 PNC light-emitting diodes (LEDs) by using PNCs with optimized didecyldimethyl ammonium bromide ligands with a current efficiency of 31.7 cd A–1 and external quantum efficiency of 9.7%, which were enhanced 16-fold compared to those of CsPbBr3 LEDs using PNCs with conventional OAm ligands.
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IJS, KILJ, NUK, PNG, UL, UM
This study aims to investigate the effects of relationship-specific resources and tailored activities on relationship performance. Based on the Industrial Marketing and Purchasing group's ...actors–resources–activities (ARA) model, this paper critically reviews the transaction-cost and organization-design literature emphasizing a negative aspect of firms' resources or activities customized to relationship counterparts that cause transaction or coordination difficulties. This paper presents the results of a quantitative study by using survey data collected from 375 business units of Japanese manufacturing firms. The results show resource specificity and activity tailoredness positively influence relationship performance. We investigated the role of vertical integration as a moderator, in order to examine the performance effects more precisely. In contrast to a proposition of the transaction-cost and organization-design literature that low (high) specificity and tailoredness fit a low (high) vertical-integration level, one of the results suggests that even under a low integration level, performance increases as relationship-specific resources increase. We explored another moderator, as per the ARA model's assumption that the nature of complementarity among heterogenic resources and between the resources and activities of different firms will significantly influence relationship performance. We found that the performance effect of wholesalers' activity tailoredness increases as manufacturers' exploitation capacities as a knowledge-based resource increase.
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GEOZS, IJS, IMTLJ, KILJ, KISLJ, NLZOH, NUK, OILJ, PNG, SAZU, SBCE, SBJE, UL, UM, UPCLJ, UPUK, ZRSKP
The deep learning (DL) approaches in smart grid (SG) describes the possibility of shifting the energy industry into a modern era of reliable and sustainable energy networks. This paper proposes a ...time-series clustering framework with multi-step time-series sequence to sequence (Seq2Seq) long short-term memory (LSTM) load forecasting strategy for households. Specifically, we investigate a clustering-based Seq2Seq LSTM electricity load forecasting model to undertake an energy load forecasting problem, where information input to the model contains individual appliances and aggregate energy as historical data of households. The original dataset is preprocessed, and forwarded to a multi-step time-series learning model which reduces the training time and guarantees convergence for energy forecasting. Furthermore, simulation results show the accuracy performance of the proposed model by validation and testing cluster data, which shows a promising potential of the proposed predictive model.
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IZUM, KILJ, NUK, PILJ, PNG, SAZU, UL, UM, UPUK
Colorectal cancer (CRC) is one of the most common causes of cancer morbidity in both sexes but shows sex differences. First, sex-specific differences in tumor recurrence and survival rates have been ...reported. For example, the development of CRC is found about 1.5 times higher and 4-8 years earlier in males compared to females, suggesting the protective role of estrogen in the disease. Furthermore, female patients have a higher risk of developing right-sided (proximal) colon cancer than male patients, which is known to have more aggressive clinical character compared to left-sided (distal) colon cancer. That is, left and right CRCs show differences in carcinogenic mechanism, that the chromosomal instability pathway is more common in left colon cancer while the microsatellite instability and serrated pathways are more common in right colon cancer. It is thought that there are sex-based differences on the background of carcinogenesis of CRC. Sex differences of CRC have two aspects, sexual dimorphism (biological differences in hormones and genes) and gender differences (non-biological differences in societal attitudes and behavior). Recently, sex difference of colon adenoma pathway and sexual dimorphism in the biology of gene and protein expression, and in endocrine cellular signaling in the CRC carcinogenesis have been accumulated. In addition, behavioral patterns can lead to differences in exposure to risk factors such as drinking or smoking, diet and physical activity. Therefore, understanding sex/gender-related biological and sociocultural differences in CRC risk will help in providing strategies for screening, treatment and prevention protocols to reduce the mortality and improve the quality of life. In this review, sex/gender differences in colon adenoma pathway and various aspects such as clinicopathological, biological, molecular, and socio-cultural aspects of CRC were described.
In this study, GaP QDs were synthesized by a facile hot injection method. The optical properties such as absorption and PL emission were investigated and finely controlled by varying synthetic ...parameters such as surfactant loading, precursor composition, and fatty acid. The obtained GaP QDs were applied as a color conversion material on LED based devices.
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Group III–Ⅴ quantum dots (QDs) are preferred over Group Ⅱ–Ⅵ materials because of their relatively mild toxicity. In this study, a facile synthetic method to obtain gallium phosphide (GaP) QDs with color conversion performance is reported. Colloidal GaP QDs were produced via a hot-injection method using an optimized combination of precursors. The products showed controllable emissions from 400 to 520 nm, depending on the band gap. High photoluminescence (PL) quantum yields of 35–40% with a full width at half maximum (FWHM) of 75 nm were achieved in the green emission region. In addition, the green-emission GaP QDs were applied as a color-conversion material for optical devices with UV and blue LED chips. An average color conversion efficiency of 15% was achieved. This study demonstrates the possibility of using GaP QDs as a competitive color-conversion material.
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GEOZS, IJS, IMTLJ, KILJ, KISLJ, NLZOH, NUK, OILJ, PNG, SAZU, SBCE, SBJE, UILJ, UL, UM, UPCLJ, UPUK, ZAGLJ, ZRSKP
Heterogeneous wireless networks where several systems with different bands coexist for multimedia service are currently in service and will be widely adopted to support various traffic demand. Under ...heterogeneous networks, a mobile station can transmit over multiple and simultaneous radio access technologies (RATs) such as WLAN, HSPA, and WCDMA LTE. Also, cognitive radio for the efficient use of underutilized/unused frequency band is successfully implemented in some networks. In this letter, we address such operational issues as air interface and band selection for a mobile and power allocation to the chosen links. An optimal solution is sought and analyzed and a distributed joint allocation algorithm is proposed to maximize total system capacity. We investigate the benefit of multiple transmissions by multiple RATs over a single transmission by a single RAT at a time, which can be interpreted as network diversity. Numerical results validate the performance enhancement of our proposed algorithm.
Background
Inactivation of
TP53
, a tumor suppressor gene, is associated with the development of several malignancies, including gastric cancer (GC). The present study aimed to evaluate the ...correlation between the overexpression of p53 and survival in different Lauren-type GCs.
Methods
From May 2003 to December 2019, 3608 GC patients treated endoscopically or surgically at the Seoul National University Bundang Hospital were enrolled for the study. Immunohistochemical staining for p53 was performed on all endoscopic and surgical gastric specimens. Clinicopathologic characteristics with Lauren classification, survival rate, and cancer recurrence were analyzed according to p53 overexpression.
Results
Among 3608 GC patients, p53 overexpression was seen in 1334 patients (37%). p53 overexpression was associated with lower depth of invasion (
P
= 0.026) and Early gastric cancer (
P
= 0.044) in intestinal-type GC, and with advanced TNM stage (
P
< 0.001) and Advanced gastric cancer (
P
< 0.001) in diffuse-type GC. The overall survival (OS) and GC-specific survival (GCSS) were significantly lower in p53 overexpression positive patients. This significance was more pronounced and enhanced in the diffuse-type GC and was absent in the intestinal-type GC. In multivariate analyses, p53 overexpression was associated with poor OS in both subtypes of GC and cancer recurrence in diffuse-type GC. (OS in intestinal-type: adjusted hazard ratio aHR = 1.423,
P
= 0.022; OS in diffuse-type: aHR = 1.401
P
= 0.035; cancer recurrence in diffuse-type: aHR = 1.502,
P
= 0.039).
Conclusion
p53 overexpression was associated with poor prognosis in GC, especially in diffuse-type. In addition, p53 overexpression was associated with early stage disease in intestinal-type GC and with advanced stage disease in diffuse-type GC.
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EMUNI, FIS, FZAB, GEOZS, GIS, IJS, IMTLJ, KILJ, KISLJ, MFDPS, NLZOH, NUK, OILJ, PNG, SAZU, SBCE, SBJE, SBMB, SBNM, UKNU, UL, UM, UPUK, VKSCE, ZAGLJ
Electricity load forecasting is an essential part of power system planning and operation, and it is crucial to make accurate predictions. The smart grid paradigm and the new energy market necessitate ...better demand-side management (DSM) and more reliable end-user forecasts to system scale. This paper proposes a time-series clustering-based probabilistic electricity future prediction for short-term load forecasting (STLF), which makes forecasts more accurate and intelligent. The weather and data noise uncertainties are considered, with the load probabilistic interval as the model's output for individual and aggregated household energy consumption. This paper adapts the logarithm of the hyperbolic cosine (log-cosh) of the error value as quantile loss and time feature with long short-term memory (LSTM) to bridge the gap. This paper presents a framework for probabilistic electric load forecasting that incorporates clustering-based quantile-LSTM learning to improve the accuracy and robustness of short-term electricity prediction. The proposed model is primarily applied to energy demand information on 15-minute and 1-hour time horizons for day-ahead prediction tasks, which are the key concerns for electricity utilities. Various state-of-the-art regression learning techniques, i.e., quantile regression forest (QRF), quantile regression neural network (QRNN), quantile gradient boosting regression tree (QGBRT), and quantile LSTM (Q-LSTM), were utilized and evaluated. The findings indicate that the proposed cluster-based probabilistic forecasting approach outperforms the existing benchmark models in terms of prediction interval coverage probability (PICP) evaluation metric.