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A Study on the Location Characteristics of Complex Cultural Space
(연구배경 및 목적) 장소를 경험함에 있어 한가지 경험의 공간보다는 문화와 쇼핑과 오락, 취미활동, 엔터테인먼트 유흥을 위한 공간과 식당, 카페 등의 편의시설들을 동시에 경험할 수 있도록 다변화의 경험으로 변화하고 있다. 문화예술 프로그램의 다양화와 질적 향상을 위하여 하나의 목적 공간이 아닌 복합문화공간의 개념 도입 등을 통해 정부나 기업은 시민과 고객의 문화에 대한 욕구를 충족시키고 있다. 이에 장소적 특성을 담은 복합문화공간은 브랜딩에 있어 더욱 부가가치가 높아지고 있다. 복합문화공간의 장소적 가치와 공간에서 제공하는 경험을 통하여 장소에 따른 공간의 특성을 연구하여 장소성을 담은 효율적인 복합문화공간의 기획을 연구하여 향후 발전적 연구에 참고가 되고자 하는 목적이 있다.
(연구방법) 선행연구를 통하여 복합문화공간의 개념 및 구성요소와 특성을 파악하여 유형과 공간적 요소의 특징을 도출하였다. 장소의 개념 및 형성 요인을 연구하였으며 복합문화공간의 장소적 가치를 분석한 후 복합문화공간 공간 요소의 장소적 특성을 위하여 연구 모형을 도출하여 연구 범위의 대상지 사례에 대입 후 결론을 도출하였다. 과정에서 장소적 가치는 문화적 가치, 사회적 가치, 경제적 가치로 분류하였으며 복합문화공간의 공간 구성요소로 역사적 문화성, 복합적 예술성, 참여적 접근성, 가변적 다양성, 차별적 심미성과 지속적 기능성을 통하여 분석하여 연구 모형으로 연결하였다. 사례는 장소성을 반영한 복합문화공간이지만 재생, 상업 공간 비슷하지만, 다른 공간을 선정하여 결과를 도출하였다.
(결과) 재생 공간으로 장소적 의미와 역사적 문화성을 갖고 있지만 경험적 접근성과 다양성을 가진 프로그램으로 지속성을 가진 복합문화공간이 문화적 가치가 높게 나왔으며 사회적 가치는 장소성보다는 경험적 요인이 높은 경우와 다양성이 높은 경우 사회적 가치가 높게 나타났으며 프로그램의 트랜드가 빠를수록 사회적 가치의 상호성이 높게 나타났다. 역사적 문화성이 높지만, 참여적 접근성과 지속적 기능성이 낮으면 경제적 가치는 낮게 나타났다.
(결론) 장소성에 대한 개념은 지리적 장소성보다는 서비스 프로그램을 통하여 지역적 특성을 반영한 장소성이 문화적 가치를 올리며 사회적 접근성을 높이며 경제적 가치를 높이는 지속성을 가져간다. 향후 더욱 다양화된 복합문화공간을 유형화하며 해외 사례도 연구하여 지속적인 연구가 계속되어야 한다.
(Background and Purpose) Experiencing places is becoming a more diverse experience wherein one can engage with convenience facilities such as culture, shopping, entertainment, hobbies, entertainment, restaurants, and cafés at the same time. To diversify and improve the quality of cultural and arts programs, governments and companies must satisfy the needs of citizens and customers by introducing the concept of a complex cultural space rather than a single target space. Accordingly, complex cultural spaces with locational characteristics are increasing their added value through branding. The purpose of this study is to examine the characteristics of a space for the experience provided in the space and the location value of the complex cultural space, and to study the planning of an efficient complex cultural space containing locationality as a reference for future developmental research.
(Method) Through prior research, the concepts, components, and characteristics of complex cultural spaces were identified, and the characteristics of tangible and spatial elements were derived. The concept and formation factors of the place were studied, and after analyzing the locational value of the complex cultural space, a research model was derived for the locational characteristics of the spatial elements of the complex cultural space, and conclusions were drawn after substituting them into the case of the target site within the scope of the study. Location values were classified into cultural, social, and economic values. As a spatial component of a complex cultural space, historical culture, complex artistry, participatory accessibility, variable diversity, differential aesthetics, and continuous functionality were analyzed and connected to a research model. This case involves a complex cultural space that reflects location; however, the results were derived by selecting similar but different spaces, such as regeneration and commerce.
(Results) Although the regeneration space is a complex cultural space with locational meaning and historical and cultural characteristics, programs with experiential accessibility and diversity showed higher cultural value when the empirical factor was higher than the locational factor and the diversity was higher; the faster the trend, the higher the social value. Economic value was higher when participatory accessibility and continuous functionality were higher than when historical and cultural characteristics were high. (Conclusions) The concept of locationality increases cultural value, social accessibility, and economic value through service programs, rather than geographical locationality. In the future, more diversified complex cultural spaces should be categorized and overseas cases should be studied for the development of research
NOx emissions prediction in diesel engines: a deep neural network approach
The reduction of various nitrogen oxide (NOx) emissions from diesel engines is an important environmental issue due to their negative impact on air quality and public health. Selective catalytic reduction (SCR) has emerged as an effective technology to mitigate NOx emissions, but predicting the performance of SCR systems remains a challenge due to the complex chemistry involved. In this study, we propose using DNN models to predict NOx emission reductions in SCR systems. Four types of datasets were created; each consisted of five variables as inputs. We evaluated the models using experimental data collected from a diesel engine equipped with an SCR system. Our results indicated that the deep neural network (DNN) model produces precise estimates for exhaust gas temperature, NOx concentration, and De-NOx efficiency. Moreover, inclusion of additional input features, such as engine speed and temperature, improved the prediction accuracy of the DNN model. The mean absolute error (MAE) values for these parameters were 3.1 °C, 3.04 ppm, and 3.65%, respectively. Furthermore, the R-squared coefficient of determination values for the estimates were 0.912, 0.983, and 0.905, respectively. Overall, this study demonstrates the potential of using DNNs to accurately predict NOx emissions from diesel engines and provides insights into the impact of input features on the performance of the model
Glofitamab plus gemcitabine and oxaliplatin (GemOx) versus rituximab-GemOx for relapsed or refractory diffuse large B-cell lymphoma (STARGLO): a global phase 3, randomised, open-label trial
Background: Glofitamab monotherapy induces durable remission in patients with relapsed or refractory diffuse large B-cell lymphoma after two or more previous therapies, but has not previously been assessed as a second-line therapy. We investigated the efficacy and safety of glofitamab plus gemcitabine-oxaliplatin (Glofit-GemOx) versus rituximab (R)-GemOx in patients with relapsed or refractory diffuse large B-cell lymphoma.
Methods: The phase 3, randomised, open-label STARGLO trial was done at 62 centres in 13 countries in Asia and Australia, Europe, and North America. We recruited transplant-ineligible patients (aged ≥18 years) with histologically confirmed relapsed or refractory diffuse large B-cell lymphoma after one or more previous therapies. Patients were randomly assigned in permuted blocks (block size of six) via an interactive voice or web response system (2:1; stratified by 1 vs ≥2 previous lines of therapy and relapsed vs refractory status) to Glofit-GemOx (intravenous gemcitabine 1000 mg/m2 and oxaliplatin 100 mg/m2 plus glofitamab step-up dosing to 30 mg; for a total of eight cycles, plus four additional cycles of glofitamab monotherapy) or R-GemOx (intravenous gemcitabine 1000 mg/m2 and oxaliplatin 100 mg/m2 plus rituximab 375 mg/m2; for a total of eight cycles). The trial independent review committee, which evaluated all response-based endpoints, was masked to treatment assignment. The primary endpoint was overall survival. Efficacy analyses were by intention to treat in all randomly assigned patients. We present results from both the primary analysis (cutoff: March 29, 2023) and updated analysis after all patients had completed study therapy (cutoff: Feb 16, 2024). Safety analyses included all patients who received any study treatment. This study is registered with ClinicalTrials.gov, NCT04408638, and is ongoing (closed to recruitment).
Findings: From Feb 23, 2021, to March 14, 2023, 274 patients were enrolled and randomly assigned to receive Glofit-GemOx (n=183) or R-GemOx (n=91). 158 (58%) patients were male and 116 (42%) were female; median age was 68 years (IQR 58-74). At the primary analysis after a median follow-up of 11·3 months (95% CI 9·6-12·7), overall survival was significantly improved with Glofit-GemOx versus R-GemOx (median not estimable [NE; 95% CI 13·8 months-NE] vs 9·0 months [7·3-14·4]; hazard ratio [HR] 0·59 [95% CI 0·40-0·89]; p=0·011). At the updated analysis after a median follow-up of 20·7 months (19·9-23·3), a consistent improvement in overall survival was observed with Glofit-GemOx versus R-GemOx (median 25·5 months [18·3-NE] vs 12·9 months [7·9-18·5]; HR 0·62 [0·43-0·88]). In the safety sets, 180 (100%) patients in the Glofit-GemOx group and 84 (96%) of 88 patients in the R-GemOx group had at least one adverse event during the study period. Cytokine release syndrome occurred in 76 (44%) of 172 glofitamab-exposed patients and was predominantly low grade. Deaths related to glofitamab or rituximab occurred in five (3%) patients in the Glofit-GemOx group and in one (1%) patient in the R-GemOx group.
Interpretation: Glofit-GemOx had a significant overall survival benefit compared with R-GemOx, supporting its use in transplant-ineligible patients with relapsed or refractory diffuse large B-cell lymphoma after one or more previous lines of therapy
Development and Validation of Deep Learning-Based Software for Automatic Analysis of Cardiovascular Borders in Lateral Chest X-ray Images
Cardiovascular border (CB) analysis is a fundamental method for detecting and assessing the severity of heart diseases using chest X-ray (CXR). This study aimed to develop and validate a deep learning-based CB automatic analysis software algorithm for quantitative analysis of lateral chest X-ray images. For detecting CB in Lateral CXR images, we utilized the Mask R- CNN. This model is an algorithm capable of accurate object detection and segmentation. We proposed more precise results using reasonable pre-processing and post-processing algorithms with this model, and suggested indicator for quantitative analysis of images. The CB detection performance of the developed model was evaluated with a precision of 99.92%, recall of 99.89%, F1 score of 99.91%, and a false positive rate per patient of 0.48. We used a developed validation dataset to verify the reliability between the CB automatic label (CB_auto) and the CB manual label (CB_hand) using the proposed CB measure index. At the 4cm point in the proposed CB measure, the highest Intraclass correlation coefficient (ICC) (0.95-0.99) was observed. Comparing the absolute difference in CB measure between the normal control group and abnormal groups at the 4cm point, significant differences were found in Tricuspid valve disease (TD) 12.7mm, Mitral valve disease (MD) 11.2mm, Pulmonary valve disease (PD) 8.5mm, and Aortic valve disease (AD) 6.8mm. The success rate of the CB measure was 91.6% in normal, 83.0% in AD, 84.5% in MD, 84.4% in PD, and 77.7% in TD. Subsequently, we conducted statistical analysis on the measured CB measure results by gender (male, female) in the normal control group. The Mean and Standard deviation in the normal control group were 25.5±9.7 for males and 16.7±8.9 for females, and the median (Interquartile ranges (IQRs)) were 25.5 (18.9-31.9) for males and 16.7 (10.7-22.6) for females. Additionally, we compared the median (IQRs) values of z-scores after fitting the model for the normal control group using the GAMLSS library. For males, normal was 0.01 (-0.69 to +0.68), AD was -0.58 (-1.51 to +0.29), MD was -0.90 (-1.62 to -0.10), PD was -0.17 (-1.03 to +0.21), and TD was -1.09 (- 1.78 to +0.30). For females, normal was 0.01 (-0.67 to +0.68), AD was -0.33 (-1.12 to +0.42), MD was -0.91 (-1.57 to -0.22), PD was -0.80 (-1.57 to +0.13), and TD was -0.90 (-1.47 to 0.00). When comparing normal control with abnormal groups, the abnormal groups generally showed lower values.Maste
PEMFC Performance Analysis with Metal Foam Flow Field : Manifold Size Effect
최근 화석 연료에 의존하는 기존 발전 시스템을 청정하고 재생 가능한 에너지 발전 시스템으로 전환하는 것은 인류의 지속 가능성을 보장하기 위해 각광받고 있다. 고분자 전해질 연료전지(PEMFC)는 고효율, 저공해 특성으로 인해 차세대 에너지원으로 주목받고 있는 친환경적인 에너지 변환 장치이다. 고분자 전해질 연료전지의 성능은 반응물의 물질 전달에 의존하며, 이는 분리판의 유로에 큰 영향을 받는다. 기존의 채널/립 형태의 유로에 비교하여, 다공성 유로는 립 영역에서의 불균일한 압력 및 수분 응축을 방지하고, 전극 면적에 반응물을 균일하게 공급하며, 생성수를 효과적으로 배출할 수 있는 장점을 제공한다. 이에 따라 최근 다공성 유로에 관한 연구가 활발히 진행되고 있다.
본 연구에서는 금속 폼 유로에서 매니폴드 크기가 연료전지 성능에 미치는 영향에 관한 실험을 수행하였고, 실험 과정에서 상대습도와 공기의 화학양론비를 조절하였다. 고습도 조건에서 매니폴드의 크기가 작아지면 물질 전달 손실이 감소하였으나, 매니폴드 크기가 가장 작은 샘플의 경우 생성수 배출의 한계로 인해 물질 전달 손실이 오히려 증가하였다. 저습도 조건에서는 물질 전달 손실의 영향이 적어 매니폴드 크기에 따른 성능 차이가 크지 않았다. 공기의 화학양론비를 증가시켰을 때, 상대습도에 관계없이 매니폴드 크기가 가장 작은 샘플의 성능이 가장 크게 향상되었지만, 저습도 조건에서는 상대적으로 성능 개선 효과가 미미하였다. 따라서 매니폴드 크기는 주로 물질 전달 손실과 관련이 있고, 매니폴드 크기의 최적화는 고전류밀도에서의 수소 연료 효율을 향상시킬 수 있는 것으로 확인되었다.|In recent years, the transformation of conventional power generation systems that rely on fossil fuels to clean and renewable energy generation systems has gained prominence to ensure human sustainability. Polymer electrolyte membrane fuel cell (PEMFC) is an environmentally friendly energy conversion device that is attracting attention as a next-generation energy source due to its high efficiency and low emission characteristics. The performance of PEMFC relies on the mass transfer of reactants, which is strongly influenced by the flow field of the bipolar plates. Compared to conventional channel/rib flow fields, porous flow fields have the advantages of preventing uneven pressure and water condensation in the rib area, uniformly supplying reactants to the electrode area, and effectively discharging water. As a result, porous flow fields have been extensively studied in recent years.
In this study, the effect of manifold size on fuel cell performance in a metal foam flow field was investigated. The experiments controlled the relative humidity and air stoichiometry. Under high relative humidity conditions, mass transfer losses decreased with smaller manifold sizes. However, for the sample with the smallest manifold size, mass transfer losses increased due to limitations in water discharge. In low relative humidity conditions, mass transfer losses were less affected, resulting insignificant performance differences based on manifold size. Increasing the air stoichiometry improved the performance of the sample with the smallest manifold size the most, regardless of relative humidity. However, the performance enhancement was relatively minor under low humidity conditions. Thus, the study confirmed that manifold size primarily affects mass transfer loss, and optimizing the manifold size can enhance hydrogen fuel efficiency at high current densities.Maste
Influence of diabetes on microbiome in prostate tissues of patients with prostate cancer
Background: Although microbiota in prostatic tissues of patients with prostate cancer have been studied, results of different studies have been inconsistent. Different ethnicity of study subjects, different study designs, and potential contaminations during sample collection and experiments might have influenced microbiome results of prostatic tissues. In this study, we analyzed microbiota and their potential functions in benign and malignant tissues of prostate cancer considering possible contaminants and host variables.
Materials and methods: A total of 118 tissue samples (59 benign tissues and 59 malignant tissues) obtained by robot-assisted laparoscopic radical prostatectomy were analyzed and 64 negative controls (from sampling to sequencing processes) were included to reduce potential contaminants.
Results: Alteration of the microbiome in prostate tissues was detected only in patients with diabetes. Furthermore, the influence of diabetes on microbiome was significant in malignant tissues. The microbiome in malignant tissues of patients with diabetes was influenced by pathologic stages. The relative abundance of Cutibacterium was reduced in the high pathologic group compared to that in the intermediate group. This reduction was related to microbial pathways increased in the high pathologic group.
Conclusion: Results of this study indicate that diabetes can influence the progression of prostate cancer with microbiome alteration in prostate tissues. Although further studies are necessary to confirm findings of this study, this study can help us understand tissue microbiome in prostate cancer and improve clinical therapy strategies
Calibration method of a three-dimensional scanner based on a line laser projector and a camera with 1-axis rotating mechanism
This study introduces a scanning system that utilizes a motor platform to mount a line laser and a camera. Two crucial parameters are considered to extract three-dimensional information from a single frame: a rotation axis and a specific point along this axis. A calibration approach for rotation axis identification is presented to determine these parameters. The rotation axis corresponds to the normal vector of the camera's movement plane and defines the rotation matrix during the scanning process. The identified point on the rotation axis serves as the translation matrix's center and represents the focal point of the camera's trajectory. A comprehensive point cloud is generated by assembling multiple frames using the scanner's rotation angle. Experimental findings substantiate the method's efficacy in enhancing the system's scanning for plane reconstruction and accuracy, and the scanning quality is much better than that of the previous approach
Maternal and Neonatal Outcomes Based on Changes in Glycosylated Hemoglobin Levels During First and Second Trimesters of Pregnancy in Women with Pregestational Diabetes: Multicenter, Retrospective Cohort Study in South Korea
This study compared glycosylated hemoglobin (HbA1c) levels in the first and second trimesters of pregnancy and assessed maternal and neonatal outcomes according to HbA1c variations among women with pregestational diabetes. This retrospective, multicenter Korean study involved mothers with diabetes who had given birth in 17 hospitals. A total of 292 women were divided into three groups based on HbA1c levels during the first and second trimesters: women with HbA1c levels maintained at <6.5% (well-controlled [WC] group); women with HbA1c ≥ 6.5% (poorly-controlled [PC] group); and women with HbA1c ≥ 6.5% in the first trimester but <6.5% in the second trimester (improved-control [IC] group). The PC group had the highest pregnancy-associated hypertension (PAH) incidence, while the incidence did not significantly differ between the WC and IC groups. The receiver operating characteristic (ROC) curve indicated that HbA1c in the second trimester could predict PAH with a cut-off value of 5.7%. The PC versus WC versus IC group showed statistically significantly higher neonatal birthweight and significantly higher rates of large for gestational age (LGA); however, those were not significantly different between the WC and IC groups. HbA1c levels in the second trimester could predict LGA, with a cut-off value of 5.4%. Therefore, the second trimester HbA1c levels were significantly associated with both maternal and neonatal outcomes
A clinical application for arterial coupling and histomorphometric comparison of internal mammary and thoracodorsal arteries for safe use
Background: In breast reconstruction, arterial coupling has been reported to be more favorable in the thoracodorsal artery (TDA) than the internal mammary artery (IMA). This technique may help overcome anastomosis in a small, deep space. Understanding the arteries' mechanical properties is crucial for breast reconstruction's safety and success.
Methods: Abdominal-based free flap breast reconstructions performed by a single surgeon between 2020 and 2022 were retrospectively analyzed. The patients were classified by microanastomosis technique (handsewn and coupler device) to compare the rate of vascular revision. Histomorphometric analysis of arterial coupling in TDA and IMA was performed in 10 fresh cadavers for comparing wall thickness and composition, including densities of elastic fiber, smooth muscle, and collagen.
Results: A total of 309 patients (339 reconstructed breasts) were included. There were 29 patients in the TDA handsewn group (A), 38 patients in the TDA coupler group (B), and 242 patients in the IMA handsewn group (C). The rates of arterial revision in groups A, B, and C were 0.00% (95%CI: 0.00%-11.03%), 2.5% (95%CI: 0.44%-12.88%), and 1.49% (95%CI: 0.58%-3.77%), respectively, with no statistically significant differences (p-value = .694). Histologically, the thickness of the tunica media and adventitia between IMA and TDA showed no significant difference. The density of elastic fiber was significantly higher in IMA (16.70%) than in TDA (0.79%) (p-value <.001).
Conclusion: The histologic characteristics of TDA are more favorable for arterial coupling than those of IMA. Arterial coupling is a safe option in situations where TDA anastomosis must be performed through a narrow and deep incision
Prediction of hospitalization and waiting time within 24 hours of emergency department patients with unstructured text data
Overcrowding of emergency departments is a global concern, leading to numerous negative consequences. This study aimed to develop a useful and inexpensive tool derived from electronic medical records that supports clinical decision-making and can be easily utilized by emergency department physicians. We presented machine learning models that predicted the likelihood of hospitalizations within 24 hours and estimated waiting times. Moreover, we revealed the enhanced performance of these machine learning models compared to existing models by incorporating unstructured text data. Among several evaluated models, the extreme gradient boosting model that incorporated text data yielded the best performance. This model achieved an area under the receiver operating characteristic curve score of 0.922 and an area under the precision-recall curve score of 0.687. The mean absolute error revealed a difference of approximately 3 hours. Using this model, we classified the probability of patients not being admitted within 24 hours as Low, Medium, or High and identified important variables influencing this classification through explainable artificial intelligence. The model results are readily displayed on an electronic dashboard to support the decision-making of emergency department physicians and alleviate overcrowding, thereby resulting in socioeconomic benefits for medical facilities