Poly[(μ6-benzene-1,3,5-tricarboxyl­ato-κ6 O 1:O 1′:O 3:O 3′:O 5:O 5′)tris­(N,N-dimethyl­formamide-κO)tris­(μ3-formato-κ2 O:O′)trimagnesium(II)]

The title complex, [Mg3(CHO2)3(C9H3O6)(C3H7NO)3]n, exhib­its a two-dimensional structure parallel to (001), which is built up from the MgII atoms and bridging carboxyl­ate ligands (3 symmetry). The MgII atom is six-coordinated by one O atom from a dimethyl­formamide mol­ecule, two O atoms from two μ6-benzene-1,3,5-tricarboxyl­ate ligands and three O atoms from three μ3-formate ligands in a distorted octa­hedral geometry

Economic lot sizing with imperfect rework derived without derivatives

This paper presents an algebraic method for solving economic production quantity (EPQ) model with imperfect rework. Conventional method for deriving optimal lot size is by using differential calculus on the cost function with the need to prove optimality first. Recent articles proposed algebraic approach to the solution of classic economic order quantity (EOQ) and EPQ model without reference to the use of derivatives. This note extends them to an EPQ model taking into consideration an imperfect rework of defective items. We demonstrate that the optimal lot size and the expected production-inventory cost for such a realistic EPQ model can be derived without derivatives

Economic lot sizing with imperfect rework derived without derivatives

This paper presents an algebraic method for solving economic production quantity (EPQ) model with imperfect rework. Conventional method for deriving optimal lot size is by using differential calculus on the cost function with the need to prove optimality first. Recent articles proposed algebraic approach to the solution of classic economic order quantity (EOQ) and EPQ model without reference to the use of derivatives. This note extends them to an EPQ model taking into consideration an imperfect rework of defective items. We demonstrate that the optimal lot size and the expected production-inventory cost for such a realistic EPQ model can be derived without derivatives

Effect of variable shipping frequency on production-distribution policy in a vendor-buyer integrated system

This paper investigates the effect of variable shipping frequency on production-distribution policy in a vendor-buyer integrated system. In a recent article Chiu et al. [1] derived the optimal replenishment lot size for an economic production quantity problem with multi-delivery and quality assurance, based on an assumption that the number of shipment is a given constant. However, in a vendor-buyer integrated system in supply chain environment, joint determination of replenishment lot size and number of shipments may help such a system to gain significant competitive advantage in terms of becoming a low-cost producer as well as having tight linkage to customer. For this reason, the present study extends the work of Chiu et al. [1] by considering shipping frequency as one of the decision variables and incorporating customer’s stock holding cost into system cost analysis. Hessian matrix equations are employed to certify the convexity of cost function that contains two decision variables, and the effect of variable shipping frequency on production-distribution policy is investigated. A numerical example is provided to demonstrate practical usage of the research result

Sixteen years post radiotherapy of nasopharyngeal carcinoma elicited multi-dysfunction along PTX and chronic kidney disease with microcytic anemia

BACKGROUND: The hypothalamic–pituitary (h-p) unit is a particularly radiosensitive region in the central nervous system. As a consequence, radiation-induced irreversible, progressively chronic onset hypopituitarism (RIH) commonly develops after radiation treatments and can result in variably impaired pituitary function, which is frequently associated with increased morbidity and mortality. CASE PRESENTATION: A 38-year-old male subject, previously having received radiotherapy for treatment of nasopharygeal carcinoma (NPCA) 16 years ago, appeared at OPD complaining about his failure in penile erection, loss of pubic hair, atrophy of external genitalia: testicles reduced to 2×1.5 cm; penile size shrunk to only 4 cm long. Characteristically, he showed extremely lowered human growth hormone, (HGH, 0.115 ng/mL), testosterone (<0.1 ng/mL), total thyroxine (tT4: 4.740 g/mL), free T4 (fT4, 0.410 ng/mL), cortisol (2.34 g/dL); lowered LH (1.37 mIU/mL) and estradiol (22 pg/mL); highly elevated TSH (7.12 IU/mL). As contrast, he had low end normal ACTH, FSH, total T3, free T3, and estriol; high end normal prolactin (11.71 ng/mL), distinctly implicating hypopituitarism-induced hypothyroidism and hypogonadism. serologically, he showed severely lowered Hb (10.6 g/dL), HCT (32.7%), MCV (77.6 fL), MCH (25.3 pg), MCHC (32.6 g/dL), and platelet count (139×103/L) with extraordinarily elevated RDW (18.2%), together with severely lowered ferritin (23.6 ng/mL) and serum iron levels; highly elevated total iron binding capacity (TIBC, 509 g/dL) and transferrin (363.4 mg/dL), suggesting microcytic anemia. Severely reduced estimated glomerular filtration rate (e-GFR) (89 mL/mim/1.73 m2) pointed to CKD2. Hypocortisolemia with hyponatremia indicated secondary adrenal insufficiency. Replacement therapy using androgen, cortisol, and Ringer’s solution has shown beneficial in improving life quality. CONCLUSIONS: To our believe, we are the first group who report such complicate PTX dysfunction with adrenal cortisol insufficiency concomitantly occurring in a single patient

Distributed Training Large-Scale Deep Architectures

Scale of data and scale of computation infrastructures together enable the current deep learning renaissance. However, training large-scale deep architectures demands both algorithmic improvement and careful system configuration. In this paper, we focus on employing the system approach to speed up large-scale training. Via lessons learned from our routine benchmarking effort, we first identify bottlenecks and overheads that hinter data parallelism. We then devise guidelines that help practitioners to configure an effective system and fine-tune parameters to achieve desired speedup. Specifically, we develop a procedure for setting minibatch size and choosing computation algorithms. We also derive lemmas for determining the quantity of key components such as the number of GPUs and parameter servers. Experiments and examples show that these guidelines help effectively speed up large-scale deep learning training

Detection of the inferred interaction network in hepatocellular carcinoma from EHCO (Encyclopedia of Hepatocellular Carcinoma genes Online)

BACKGROUND: The significant advances in microarray and proteomics analyses have resulted in an exponential increase in potential new targets and have promised to shed light on the identification of disease markers and cellular pathways. We aim to collect and decipher the HCC-related genes at the systems level. RESULTS: Here, we build an integrative platform, the Encyclopedia of Hepatocellular Carcinoma genes Online, dubbed EHCO , to systematically collect, organize and compare the pileup of unsorted HCC-related studies by using natural language processing and softbots. Among the eight gene set collections, ranging across PubMed, SAGE, microarray, and proteomics data, there are 2,906 genes in total; however, more than 77% genes are only included once, suggesting that tremendous efforts need to be exerted to characterize the relationship between HCC and these genes. Of these HCC inventories, protein binding represents the largest proportion (~25%) from Gene Ontology analysis. In fact, many differentially expressed gene sets in EHCO could form interaction networks (e.g. HBV-associated HCC network) by using available human protein-protein interaction datasets. To further highlight the potential new targets in the inferred network from EHCO, we combine comparative genomics and interactomics approaches to analyze 120 evolutionary conserved and overexpressed genes in HCC. 47 out of 120 queries can form a highly interactive network with 18 queries serving as hubs. CONCLUSION: This architectural map may represent the first step toward the attempt to decipher the hepatocarcinogenesis at the systems level. Targeting hubs and/or disruption of the network formation might reveal novel strategy for HCC treatment