Plant Location Selection for Food Production by Considering the Regional and Seasonal Supply Vulnerability of Raw Materials

A production capacity analysis considering market demand and raw materials is very important to design a new plant. However, in the food processing industry, the supply uncertainty of raw materials is very high, depending on the production site and the harvest season, and further, it is not straightforward to analyze too complex food production systems by using an analytical optimization model. For these reasons, this study presents a simulation-based decision support model to select the right location for a new food processing plant. We first define three supply vulnerability factors from the standpoint of regional as well as seasonal instability and present an assessment method for supply vulnerability based on fuzzy quantification. The evaluated vulnerability scores are then converted into raw material supply variations for food production simulation to predict the quarterly production volume of a new food processing plant. The proposed selection procedure is illustrated using a case study of semiprocessed kimchi production. The best plant location is proposed where we can reduce and mitigate risks when supplying raw material, thereby producing a target production volume steadily

Identification of protein functions using a machine-learning approach based on sequence-derived properties

<p>Abstract</p> <p>Background</p> <p>Predicting the function of an unknown protein is an essential goal in bioinformatics. Sequence similarity-based approaches are widely used for function prediction; however, they are often inadequate in the absence of similar sequences or when the sequence similarity among known protein sequences is statistically weak. This study aimed to develop an accurate prediction method for identifying protein function, irrespective of sequence and structural similarities.</p> <p>Results</p> <p>A highly accurate prediction method capable of identifying protein function, based solely on protein sequence properties, is described. This method analyses and identifies specific features of the protein sequence that are highly correlated with certain protein functions and determines the combination of protein sequence features that best characterises protein function. Thirty-three features that represent subtle differences in local regions and full regions of the protein sequences were introduced. On the basis of 484 features extracted solely from the protein sequence, models were built to predict the functions of 11 different proteins from a broad range of cellular components, molecular functions, and biological processes. The accuracy of protein function prediction using random forests with feature selection ranged from 94.23% to 100%. The local sequence information was found to have a broad range of applicability in predicting protein function.</p> <p>Conclusion</p> <p>We present an accurate prediction method using a machine-learning approach based solely on protein sequence properties. The primary contribution of this paper is to propose new <it>PNPRD </it>features representing global and/or local differences in sequences, based on positively and/or negatively charged residues, to assist in predicting protein function. In addition, we identified a compact and useful feature subset for predicting the function of various proteins. Our results indicate that sequence-based classifiers can provide good results among a broad range of proteins, that the proposed features are useful in predicting several functions, and that the combination of our and traditional features may support the creation of a discriminative feature set for specific protein functions.</p

Ionothermal Synthesis of Metal-Organic Framework

Ionothermal synthesis employs ionic liquids for synthesis of metal organic frameworks (MOFs) as solvent and template. The cations and anions of ionic liquids may be finely adjusted to produce a great variety of reaction environments and thus frameworks. Organisation of the structures synthesised from related ionic liquid combinations give rise to provocative chemical trends that may be used to predict future outcomes. Further analysis of their structures is possible by reducing the complex framework to its underlying topology, which by itself brings more precision to prediction. Through reduction, many seemingly different, but related classes of structures may be merged into larger groups and provide better understanding of the nanoscopic structures and synthesis conditions that gave rise to them. Ionothermal synthesis has promised to enable us to effectively plan the synthesis ahead for a given purpose. However, for its promise to be kept, several difficult limitations must be overcome, including the inseparable cations from the solvent that reside in the framework pore

A Factor Analysis of Urban Railway Casualty Accidents and Establishment of Preventive Response Systems

AbstractSince the commencement of urban railways in 1974 and KTX service in 2014, the use of railways has been steadily increasing. The number of people using rail transportation has been steadily rising. As a result, this has also led to an increase in the number of passenger-related accidents that are occurring within railway stations. In an effort to prevent such accidents, much of the rail operation system is now automated. Nevertheless, the potential risks of railway accidents are very much present today. This study has utilized the railway accident databases of rail operators to allow for analysis of different types of railway accidents, age of accident victims, gender of accident victims, pedestrian facilities involved in accidents, passengers involved in accidents, and underlying causes of rail accidents. Based on these statistics and analyses, this paper proposes the development of a railway safety education program and the establishment of railway safety education centers as a means of preventing railway accidents

Additive Value of B-Type Natriuretic Peptide on Rest 201Tl-Dipyridamole Stress 99mTc-Sestamibi Gated Myocardial SPECT in Patients with Normal Left Ventricular Systolic Function

We evaluated whether BNP has additive value to SPECT in patients with normal left ventricular (LV) systolic function. Data from 224 consecutive patients who underwent rest 201Tl-dipyridamole stress 99mTc-sestamibi gated SPECT and coronary angiography due to chest pain were analyzed. Patients with true positive SPECT showed significant higher BNP level than those with false positive defect (38.5 (19.0–79.8) versus 19.0 (9.3–35.8), P = .01). Patients with true negative SPECT also showed significantly lower BNP level than those with false negative SPECT (39.0 (23.0–77.0) versus 22.0 (15.0–43.0), P = .002). In multivariate analyses, elevated BNP level (using a cut-off value of 23.0 pg/mL) was the strongest and independent predictor of CAD in overall patients (OR 2.75, 95% CI: 1.50–5.023, P = .001) and patients with positive SPECT (OR 3.34, 95% CI: 1.51–7.37, P = .003). The area under the receiver-operating characteristic curve for CAD in overall patients and patients with positive SPECT was 0.673 (95% CI: 0.603–0.743, P < .001) and 0.694 (95% CI: 0.602–0.786, P < .001), respectively. This study suggests that BNP level has additive diagnostic value to SPECT findings in predicting CAD in patients with normal LV systolic function

Correlation of hypoxia inducible transcription factor in breast cancer and SUVmax of F-18 FDG PET/CT

BACKGROUND: Tumor hypoxia induces the expression of several genes via the hypoxia-inducible transcription factor-1 alpha (HIF-1a). It is associated with the prognosis of several cancers. We studied the immunohistochemical expression of HIF-1a in patients with invasive ductal cancer (IDC) of the breast and the possible correlation with the maximum standardized uptake value of the primary tumor (pSUVmax) as well as other biological parameters. Prognostic significance of pSUVmax and expression of HIF-1a for the prediction of progression-free survival (PFS) was also assessed. MATERIAL AND METHODS: Two-hundred seven female patients with IDC who underwent pretreatment fluorine-18 fluorodeoxyglucose positron emission tomography/computed tomography (F-18 FDG PET/CT) were enrolled. The pSUVmax was compared with clinicopathological parameters including estrogen receptor (ER), progesterone receptor (PR), human epidermal growth factor receptor 2 (HER2), axillary lymph node (LN) metastasis, stage and HIF-1a expression. The prognostic value of pSUVmax for PFS was assessed using the Kaplan-Meier method. RESULTS: pSUVmax was significantly higher in patients with HIF-1a expression ≥ 2 compared to patients with HIF-1a expression &lt; 2 (5.2 ± 4.5 vs. 3.7 ± 3.1, p = 0.008). pSUVmax was also significantly higher in higher stage (p &lt; 0.000001), ER-negative tumors (p &lt; 0.0001), PR-negative tumors (p = 0.0011) and positive LN metastasis (p = 0.0013). pSUVmax was significantly higher in patients with progression compared to patients who were disease-free (6.8 ± 4.4 vs. 4.1 ± 3.7, p = 0.0005). A receiver-operating characteristic curve demonstrated a pSUVmax of 6.51 to be the optimal cutoff for predicting PFS (sensitivity: 53.6%, specificity: 86.0%). Patients with high pSUVmax (&gt; 6.5) had significantly shorter PFS compared to patients with low pSUVmax (p &lt; 0.0001). CONCLUSIONS: pSUVmax on pretreatment F-18 FDG PET/ CT reflect expression of HIF-1a and can be used as a good surrogate marker for the prediction of progression in patients with IDC. The amount of FDG uptake is determined by the presence of glucose metabolism and hypoxia in breast cancer cell

Clinical characteristics of acute kidney injury in patients with glyphosate surfactant herbicide poisoning

Background In this study, we investigated the clinical characteristics of acute kidney injury (AKI) in patients with glyphosate surfactant herbicide (GSH) poisoning. Methods This study was performed between 2008 and 2021 and included 184 patients categorized into the AKI (n = 82) and non-AKI (n = 102) groups. The incidence, clinical characteristics, and severity of AKI were compared between the groups based on the Risk of renal dysfunction, Injury to the kidney, Failure or Loss of kidney function, and End-stage kidney disease (RIFLE) classification. Results The incidence of AKI was 44.5%, of which 25.0%, 6.5%, and 13.0% of patients were classified into the Risk, Injury, and Failure categories, respectively. Patients in the AKI group were older (63.3 ± 16.2 years vs. 57.4 ± 17.5 years, p = 0.02) than those in the non-AKI group. The length of hospitalization was longer (10.7 ± 12.1 days vs. 6.5 ± 8.1 days, p = 0.004) and hypotensive episodes occurred more frequently in the AKI group (45.1% vs. 8.8%, p < 0.001). Electrocardiographic (ECG) abnormalities on admission were more frequently observed in the AKI group than in the non-AKI group (80.5% vs. 47.1%, p < 0.001). Patients in the AKI group had poorer renal function (estimated glomerular filtration rate at the time of admission, 62.2 ± 22.9 mL/min/1.73 m2 vs. 88.9 ± 26.1 mL/min/1.73 m2, p < 0.001) on admission. The mortality rate was higher in the AKI group than in the non-AKI group (18.3% vs. 1.0%, p < 0.001). Multiple logistic regression analysis showed that hypotension and ECG abnormalities upon admission were significant predictors of AKI in patients with GSH poisoning. Conclusion The presence of hypotension on admission may be a useful predictor of AKI in patients with GSH intoxication

Significance of the Epithelial Collar on the Subepithelial Connective Tissue Graft

Peer Reviewedhttps://deepblue.lib.umich.edu/bitstream/2027.42/142284/1/jper0924.pd

Electrical current suppression in Pd-doped vanadium pentoxide nanowires caused by reduction in PdO due to hydrogen exposure

Pd nanoparticle-doped vanadium pentoxide nanowires (Pd-VONs) were synthesized. Electrical current suppression was observed when the Pd-VON was exposed to hydrogen gas, which cannot be explained by the work function changes mentioned in previous report such as Pd-doped carbon nanotubes and SnO 2 nanowires. Using the x-ray photoelectron spectroscopy, we found that the reduction in PdO due to hydrogen exposure plays an important role in the current suppression of the Pd-VON.open4