Synergy analysis of collaborative supply chain management in energy systems using multi-period

Abstract Energy, a fundamental entity of modern life, is usually produced using fossil fuels as the primary raw material. A consequence of burning fossil fuels is the emission of environmentally harmful substances. Energy production systems generate steam and electricity that are served to different process customers to satisfy their energy requirement. The improvement of economical and environmental performance of energy production systems is a major issue due to central role of energy in every industrial activity. A systematic approach to identify the synergy among different energy systems is addressed in this paper. The multi-period and discrete-continuous nature of the energy production systems including investment costs are modeled using MILP. The proposed approach is applied on two examples that are simplified versions of an industrial problem. It is shown that the approach presented in this paper is very effective in identifying the synergy among different companies to improve their economical and environmental performance significantly

Distribution of local 137Cs anomalies on the seafloor near the Fukushima Dai-ichi Nuclear Power Plant

An estimated 3.5 ± 0.7 × 1015 Bq of 137Cs is thought to have been discharged into the ocean following the melt down at Fukushima Dai-ichi Nuclear Power Plant (F1NPP). While efforts have been made to monitor seafloor radiation levels, the sampling techniques used cannot capture the continuous distribution of radionuclides. In this work, we apply in situ measurement techniques using a towed gamma ray spectrometer to map the continuous distribution of 137Cs on the seafloor within 20 km of the F1NPP. The results reveal the existence of local 137Cs anomalies, with levels of 137Cs an order of magnitude higher than the surrounding seafloors. The sizes of the anomalies mapped in this work range from a few meters to a few hundreds of meters in length, and it is demonstrated that the distribution of these anomalies is strongly influenced by meter scale features of the terrain

Good Clinical Response to Erlotinib in a Non-Small Cell Lung Cancer Patient Harboring Multiple Brain Metastases and a Double Active Somatic Epidermal Growth Factor Gene Mutation

Recently, 2 small molecule kinase inhibitors (TKIs), targeting epidermal growth factor receptor (EGFR), have proven effective in the treatment of non-small cell lung cancer. However, it is unknown whether the EGFR double activating mutation of L858R in exon 21 and the in-frame deletion in exon 19 is a predictor of the effectiveness of EGFR-TKIs. We report for the first time a case of non-small cell lung cancer with central nervous system metastases harboring a rare EGFR double activating mutation who showed a good clinical response to erlotinib, regardless of his poor performance status, as swallowing is not possible. Therefore, we suggest that erlotinib may become a therapeutic choice in cases of central nervous system metastases even with poor performance status

Outcome of Surgical Treatment for Metastatic Vertebra Bone Tumor in Advanced Lung Cancer

Background: Spinal metastases of patients with advanced stage lung cancer are an important target for palliative therapy, because their incidence is high, and they often cause severe symptoms and worsen the quality of life. Surgery is one of the most effective treatment options, but the indication of surgery is unclear as the procedure is invasive and patients with spinal metastasis have a rather short life expectancy. Furthermore, there have been few studies that have focused on lung cancer with poor prognosis. Methods: We reviewed all of the cases of lung cancer from January 1999 to July 2007 in the Department of Respiratory Medicine, Kyoto University Hospital, Japan. Thirteen patients with metastatic spinal tumor of lung cancer underwent surgery, and all of them had a poor performance status score (3 or 4). Results: Neurological improvement by at least 1 Frankel grade was seen in 10 of 14 cases (71%). Improvement of the movement capacity was noted in 9 of 14 cases (64%), and pain improvement was noted in 12 of 14 (86%). Median postoperative survival was 5 months (1–25 months). In particular, the group with a good postoperative performance status score (0–2) was shown to have a better median postoperative survival of 13 months. Conclusions: Surgical treatment for symptomatic metastatic spinal tumor of lung cancer can improve quality of life in a substantially high percentage of patients. Surgery should be considered even if preoperative performance status is poor

Expectant management of a herniated amniotic sac presenting as silent uterine rupture: a case report and literature review.

Foetal membranes bulging into the abdominal cavity is a unique initial manifestation of silent or complete uterine rupture during pregnancy. Since silent uterine rupture has potential risk for complete uterine rupture, which leads to acute life-threatening complications for both the mother and baby, it is difficult to determine whether to manage expectantly or surgically, including repair of the uterine wall or termination of the pregnancy, especially in the early second trimester. We present here a case of a herniated amniotic sac with overstretched uterine wall of the fundus presenting as silent uterine rupture, which was incidentally detected on routine ultrasonography at 18 weeks' gestation in a 38-year-old primigravida with a history of myomectomy for diffuse uterine leiomyomatosis. Magnetic resonance imaging examination revealed that the myometrium thickness was fully maintained at the site of the foetal membranes ballooning. The pregnancy was therefore managed expectantly and continued to successful delivery at 30 weeks' gestation. The precise assessment of the uterine wall may be essential to manage a herniated amniotic sac presenting as silent uterine rupture and to optimise the outcome of the pregnancy. We review all cases of a herniated amniotic sac out of focally overstretched uterine wall before 34 weeks' gestation

Distance determination of molecular clouds in the 1st quadrant of the Galactic plane using deep learning : I. Method and Results

Machine learning has been successfully applied in varied field but whether it is a viable tool for determining the distance to molecular clouds in the Galaxy is an open question. In the Galaxy, the kinematic distance is commonly employed as the distance to a molecular cloud. However, there is a problem in that for the inner Galaxy, two different solutions, the ``Near'' solution, and the ``Far'' solution, can be derived simultaneously. We attempted to construct a two-class (``Near'' or ``Far'') inference model using a Convolutional Neural Network (CNN), a form of deep learning that can capture spatial features generally. In this study, we used the CO dataset toward the 1st quadrant of the Galactic plane obtained with the Nobeyama 45-m radio telescope (l = 62-10 degree, |b| < 1 degree). In the model, we applied the three-dimensional distribution (position-position-velocity) of the 12CO (J=1-0) emissions as the main input. The dataset with ``Near'' or ``Far'' annotation was made from the HII region catalog of the infrared astronomy satellite WISE to train the model. As a result, we could construct a CNN model with a 76% accuracy rate on the training dataset. By using the model, we determined the distance to molecular clouds identified by the CLUMPFIND algorithm. We found that the mass of the molecular clouds with a distance of < 8.15 kpc identified in the 12CO data follows a power-law distribution with an index of about -2.3 in the mass range of M >10^3 Msun. Also, the detailed molecular gas distribution of the Galaxy as seen from the Galactic North pole was determined.Comment: 29 pages, 12 figure

The respiratory microbiome associated with chronic obstructive pulmonary disease comorbidity in non‐small cell lung cancer

博士（医学）甲日本医科大学202