345 research outputs found
Artificial Intelligence in Supply Chain Operations Planning: Collaboration and Digital Perspectives
[EN] Digital transformation provide supply chains (SCs) with extensive accurate data that should be combined with analytical techniques to improve their management. Among these techniques Artificial Intelligence (AI) has proved their suitability, memory and ability to manage uncertain and constantly changing information. Despite the fact that a number of AI literature reviews exist, no comprehensive review of reviews for the SC operations planning has yet been conducted. This paper aims to provide a comprehensive review of AI literature reviews in a structured manner to gain insights into their evolution in incorporating new ICTs and collaboration. Results show that hybrization man-machine and collaboration and ethical aspects are understudied.This research has been funded by the project entitled NIOTOME (Ref. RTI2018-102020-B-I00) (MCI/AEI/FEDER, UE). The first author was supported by the Generalitat Valenciana (Conselleria de Educación, Investigación, Cultura y Deporte) under Grant ACIF/2019/021.Rodríguez-Sánchez, MDLÁ.; Alemany Díaz, MDM.; Boza, A.; Cuenca, L.; Ortiz Bas, Á. (2020). Artificial Intelligence in Supply Chain Operations Planning: Collaboration and Digital Perspectives. IFIP Advances in Information and Communication Technology. 598:365-378. https://doi.org/10.1007/978-3-030-62412-5_30S365378598Lezoche, M., Hernandez, J.E., Alemany, M.M.E., Díaz, E.A., Panetto, H., Kacprzyk, J.: Agri-food 4.0: a survey of the supply chains and technologies for the future agriculture. Comput. Ind. 117, 103–187 (2020)Stock, J.R., Boyer, S.L.: Developing a consensus definition of supply chain management: a qualitative study. Int. J. Phys. Distrib. Logistics Manag. 39(8), 690–711 (2009)Min, H.: Artificial intelligence in supply chain management: theory and applications. Int. J. Logistics Res. Appl. 13(1), 13–39 (2010). https://doi.org/10.1080/13675560902736537Hariri, R.H., Fredericks, E.M., Bowers, K.M.: Uncertainty in big data analytics: survey, opportunities, and challenges. J. Big Data 6(1), 1–16 (2019). https://doi.org/10.1186/s40537-019-0206-3Duan, Y., Edwards, J.S., Dwivedi, Y.K.: Artificial intelligence for decision making in the era of Big Data – evolution, challenges and research agenda. Int. J. Inf. Manage. 48(2019), 63–71 (2019). https://doi.org/10.1016/j.ijinfomgt.2019.01.021McCarthy, J., Minsky, M.L., Rochester, N., Shannon, C.E.: A proposal for the dartmouth summer research project on artificial intelligence. AI Mag. 27(4), 12–14 (2006)Barr, A., Feigenbaum, E.A.: The Handbook of Artificial Intelligence, vol. 2. Heuristech: William Kaufmann, Pitman (1982)High-Level Expert Group on Artificial Intelligence, European Commission. A definition of AI: main capabilities and disciplines (2019)Cioffi, R., Travaglioni, M., Piscitelli, G., Petrillo, A., De Felice, F.: Artificial intelligence and machine learning applications in smart production: progress, trends, and directions. Sustainability (Switzerland) 12(2) (2020). https://doi.org/10.3390/su12020492Cheng, L., Yu, T.: A new generation of AI: a review and perspective on machine learning technologies applied to smart energy and electric power systems. Int. J. Energy Res. 43(6), 1928–1973 (2019). https://doi.org/10.1002/er.4333Duan, Y., Edwards, J.S., Dwivedi, Y.K.: Artificial intelligence for decision-making in the era of big data. Evolution, challenges and research agenda. Int. J. Inf. Manag. 48, 63–71 (2019)Varshney, S., Jigyasu, R., Sharma, A., Mathew, L.: Review of various artificial intelligence techniques and its applications. IOP Conf. Ser. Mater. Sci. Eng. 594(1) (2019)Cheng, L., Yu, T.: A new generation of AI: a review and perspective on machine learning technologies applied to smart energy and electric power systems. Int. J. Energy Res. 43, 1928–1973 (2019)Seuring, S., Müller, M.: From a literature review to a conceptual framework for sustainable supply chain management. J. Clean. Prod. 16(15), 1699–1710 (2008). https://doi.org/10.1016/j.jclepro.2008.04.020Metaxiotis, K.S., Askounis, D., Psarras, J.: Expert Systems In Production Planning And Scheduling: A State-Of-The-Art Survey. J. Intell. Manuf. 13(4), 253–260 (2002). https://doi.org/10.1023/A:1016064126976Power, Y., Bahri, P.A.: Integration techniques in intelligent operational management: a review. Knowl. Based Syst. 18(2–3), 89–97 (2005). https://doi.org/10.1016/j.knosys.2004.04.009Shen, W., Hao, Q., Yoon, H.J., Norrie, D.H.: Applications of agent-based systems in intelligent manufacturing: an updated review. Adv. Eng. Inform. 20(4), 415–431 (2006). https://doi.org/10.1016/j.aei.2006.05.004Kobbacy, K.A.H., Vadera, S., Rasmy, M.H.: AI and OR in management of operations: history and trends. J. Oper. Res. Soc. 58(1), 10–28 (2007). https://doi.org/10.1057/palgrave.jors.2602132Zhang, W.J., Xie, S.Q.: Agent technology for collaborative process planning: a review. Int. J. Adv. Manuf. Technol. 32(3), 315–325 (2007). https://doi.org/10.1007/s00170-005-0345-xIbáñez, O., Cordón, O., Damas, S., Magdalena, L.: A review on the application of hybrid artificial intelligence systems to optimization problems in operations management. In: Corchado, E., Wu, X., Oja, E., Herrero, Á., Baruque, B. (eds.) HAIS 2009. LNCS (LNAI), vol. 5572, pp. 360–367. Springer, Heidelberg (2009). https://doi.org/10.1007/978-3-642-02319-4_43Kobbacy, K.A.H., Vadera, S.: A survey of AI in operations management from 2005 to 2009. J. Manuf. Technol. Manag. 22(6), 706–733 (2011). https://doi.org/10.1108/17410381111149602Guo, Z.X., Wong, W.K., Leung, S.Y.S., Li, M.: Applications of artificial intelligence in the apparel industry: a review. Text. Res. J. 81(18), 1871–1892 (2011). https://doi.org/10.1177/0040517511411968Priore, P., Gómez, A., Pino, R., Rosillo, R.: Dynamic scheduling of manufacturing systems using machine learning: an updated review. Artif. Intell. Eng. Des. Anal. Manuf. AIEDAM 28(1), 83–97 (2014). https://doi.org/10.1017/S0890060413000516Renzi, C., Leali, F., Cavazzuti, M., Andrisano, A.: A review on artificial intelligence applications to the optimal design of dedicated and reconfigurable manufacturing systems. Int. J. Adv. Manuf. Technol. 72(1–4), 403–418 (2014). https://doi.org/10.1007/s00170-014-5674-1Ngai, E.W.T., Peng, S., Alexander, P., Moon, K.K.L.: Decision support and intelligent systems in the textile and apparel supply chain: an academic review of research articles. Expert Syst. Appl. 41(1), 81–91 (2014). https://doi.org/10.1016/j.eswa.2013.07.013Rooh, U.A., Li, A., Ali, M.M.: Fuzzy, neural network and expert systems methodologies and applications - a review. J. Mob. Multimedia 11, 157–176 (2015)Bello, O., Teodoriu, C., Yaqoob, T., Oppelt, J., Holzmann, J., Obiwanne, A.: Application of artificial intelligence techniques in drilling system design and operations: a state of the art review and future research pathways. In: Society of Petroleum Engineers - SPE Nigeria Annual International Conference and Exhibition (2016)Arvitrida, N.I.: A review of agent-based modeling approach in the supply chain collaboration context. IOP Conf. Ser. Mater. Sci. Eng. 337(1) (2018). https://doi.org/10.1088/1757-899x/337/1/012015Zanon, L.G., Carpinetti, L.C.R.: Fuzzy cognitive maps and grey systems theory in the supply chain management context: a literature review and a research proposal. In: IEEE International Conference on Fuzzy Systems, July 2018, pp. 1–8 (2018). https://doi.org/10.1109/fuzz-ieee.2018.8491473Burggräf, P., Wagner, J., Koke, B.: Artificial intelligence in production management: a review of the current state of affairs and research trends in academia. In: 2018 International Conference on Information Management and Processing, ICIMP 2018, January 2018, pp. 82–88 (2018). https://doi.org/10.1109/icimp1.2018.8325846Diez-Olivan, A., Del Ser, J., Galar, D., Sierra, B.: Data fusion and machine learning for industrial prognosis: trends and perspectives towards Industry 4.0. Inf. Fusion 50, 92–111 (2019). https://doi.org/10.1016/j.inffus.2018.10.005Ni, D., Xiao, Z., Lim, M.K.: A systematic review of the research trends of machine learning in supply chain management. Int. J. Mach. Learn. Cybernet. 11(7), 1463–1482 (2019). https://doi.org/10.1007/s13042-019-01050-0Ning, C., You, F.: Optimization under uncertainty in the era of big data and deep learning: when machine learning meets mathematical programming. Comput. Chem. Eng. 125, 434–448 (2019). https://doi.org/10.1016/j.compchemeng.2019.03.034Okwu, M.O., Nwachukwu, A.N.: A review of fuzzy logic applications in petroleum exploration, production and distribution operations. J. Petrol. Explor. Prod. Technol. 9(2), 1555–1568 (2018). https://doi.org/10.1007/s13202-018-0560-2Weber, F.D., Schütte, R.: State-of-the-art and adoption of artificial intelligence in retailing. Digit. Policy Regul. Gov. 21(3), 264–279 (2019). https://doi.org/10.1108/DPRG-09-2018-0050Giri, C., Jain, S., Zeng, X., Bruniaux, P.: A detailed review of artificial intelligence applied in the fashion and apparel industry. IEEE Access 7, 95376–95396 (2019). https://doi.org/10.1109/ACCESS.2019.2928979Leo Kumar, S.P.: Knowledge-based expert system in manufacturing planning: State-of-the-art review. Int. J. Prod. Res. 57(15–16), 4766–4790 (2019). https://doi.org/10.1080/00207543.2018.1424372Barua, L., Zou, B., Zhou, Y.: Machine learning for international freight transportation management: a comprehensive review. Res. Transp. Bus. Manag. (2020). https://doi.org/10.1016/j.rtbm.2020.100453Chai, J., Ngai, E.W.T.: Decision-making techniques in supplier selection: recent accomplishments and what lies ahead. Expert Syst. Appl. 140 (2020). https://doi.org/10.1016/j.eswa.2019.112903Usuga Cadavid, J.P., Lamouri, S., Grabot, B., Pellerin, R., Fortin, A.: Machine learning applied in production planning and control: a state-of-the-art in the era of industry 4.0. J. Intell. Manuf. 31(6), 1531–1558 (2020). https://doi.org/10.1007/s10845-019-01531-7Ekramifard, A., Amintoosi, H., Seno, A.H., Dehghantanha, A., Parizi, R.M.: A systematic literature review of integration of blockchain and artificial intelligence. In: Choo, K.-K.R., Dehghantanha, A., Parizi, R.M. (eds.) Blockchain Cybersecurity, Trust and Privacy. AIS, vol. 79, pp. 147–160. Springer, Cham (2020). https://doi.org/10.1007/978-3-030-38181-3_8Vrbka, J., Rowland, Z.: Using artificial intelligence in company management. In: Ashmarina, S.I., Vochozka, M., Mantulenko, V.V. (eds.) ISCDTE 2019. LNNS, vol. 84, pp. 422–429. Springer, Cham (2020). https://doi.org/10.1007/978-3-030-27015-5_51Leslie, D.: Understanding artificial intelligence ethics and safety: a guide for the responsible design and implementation of AI systems in the public sector. The Alan Turing Institute (2019)Queiroz, M.M., Ivanov, D., Dolgui, A., et al.: Impacts of epidemic outbreaks on supply chains: mapping a research agenda amid the COVID-19 pandemic through a structured literature review. Ann Oper Res (2020). https://doi.org/10.1007/s10479-020-03685-
Suitable thicknesses of base metal and interlayer, and evolution of phases for Ag/Sn/Ag transient liquid-phase joints used for power die attachment
Both real Si insulated gate bipolar transistors (IGBT) with conventional Ni\Ag metallization and a dummy Si die with thickened Ni\Ag metallization have been bonded on Ag foils electroplated with 2.7 m and 6.8 m thick Sn as an interlayer at 250ºC for 0 min, 40 min and 640 min. From microstructure characterization of the resulting joints, suitable thicknesses are suggested for the Ag base metal and the Sn interlayer for Ag/Sn/Ag transient liquid phase (TLP) joints used in power die attachment, and the diffusivities of Ag and Sn in the Ag phase are extracted. In combination with the kinetic constants of Ag3Sn growth and diffusivities of Ag and Sn in Ag reported in the literature, the extracted diffusivities of Ag and Sn in Ag phase are also used to simulate and predict the diffusion-controlled growth and evolution of phases in the Ag/Sn/Ag TLP joints during an extended bonding process and in service
Seroepidemiology of human Toxoplasma gondii infection in China
<p>Abstract</p> <p>Background</p> <p>Toxoplasmosis is an important zoonotic parasitic disease worldwide. In immune competent individuals, <it>Toxoplasma gondii </it>preferentially infects tissues of central nervous systems, which might be an adding factor of certain psychiatric disorders. Congenital transmission of <it>T. gondii </it>during pregnancy has been regarded as a risk factor for the health of newborn infants. While in immune-compromised individuals, the parasite can cause life-threatening infections. This study aims to investigate the prevalence of <it>T. gondii </it>infection among clinically healthy <b>i</b>ndividuals and patients with psychiatric disorders in China and to identify the potential risk factors related to the vulnerability of infection in the population.</p> <p>Methods</p> <p>Serum samples from 2634 healthy individuals and 547 patients with certain psychiatric disorders in Changchun and Daqing in the northeast, and in Shanghai in the south of China were examined respectively for the levels of anti-<it>T. gondii </it>IgG by indirect ELISA and a direct agglutination assay. Prevalence of <it>T. gondii </it>infection in the Chinese population in respect of gender, age, residence and health status was systematically analyzed.</p> <p>Results</p> <p>The overall anti-<it>T. gondii </it>IgG prevalence in the study population was 12.3%. In the clinically healthy population 12.5% was sero-positive and in the group with psychiatric disorders 11.3% of these patients were positive with anti-<it>T. gondii </it>IgG. A significant difference (P = 0.004) was found between male and female in the healthy population, the seroprevalence was 10.5% in men versus 14.3% in women. Furthermore, the difference of <it>T. gondii </it>infection rate between male and female in the 20-19 year's group was more obvious, with 6.4% in male population and 14.6% in female population.</p> <p>Conclusion</p> <p>A significant higher prevalence of <it>T. gondii </it>infection was observed in female in the clinically healthy population. No correlation was found between <it>T. gondii </it>infection and psychiatric disorders in this study. Results suggest that women are more exposed to <it>T. gondii </it>infection than men in China. The data argue for deeper investigations for the potential risk factors that threat the female populations.</p
Lung fibroblasts from patients with emphysema show markers of senescence in vitro
BACKGROUND: The loss of alveolar walls is a hallmark of emphysema. As fibroblasts play an important role in the maintenance of alveolar structure, a change in fibroblast phenotype could be involved in the pathogenesis of this disease. In a previous study we found a reduced in vitro proliferation rate and number of population doublings of parenchymal lung fibroblasts from patients with emphysema and we hypothesized that these findings could be related to a premature cellular aging of these cells. In this study, we therefore compared cellular senescence markers and expression of respective genes between lung fibroblasts from patients with emphysema and control patients without COPD. METHODS: Primary lung fibroblasts were obtained from 13 patients with moderate to severe lung emphysema (E) and 15 controls (C) undergoing surgery for lung tumor resection or volume reduction (n = 2). Fibroblasts (8E/9C) were stained for senescence-associated β-galactosidase (SA-β-Gal). In independent cultures, DNA from lung fibroblasts (7E/8C) was assessed for mean telomere length. Two exploratory 12 k cDNA microarrays were used to assess gene expression in pooled fibroblasts (3E/3C). Subsequently, expression of selected genes was evaluated by quantitative PCR (qPCR) in fibroblasts of individual patients (10E/9C) and protein concentration was analyzed in the cell culture supernatant. RESULTS: The median (quartiles) percentage of fibroblasts positive for SA-β-Gal was 4.4 (3.2;4.7) % in controls and 16.0 (10.0;24.8) % in emphysema (p = 0.001), while telomere length was not different. Among the candidates for differentially expressed genes in the array (factor ≥ 3), 15 were upregulated and 121 downregulated in emphysema. qPCR confirmed the upregulation of insulin-like growth factor-binding protein (IGFBP)-3 and IGFBP-rP1 (p = 0.029, p = 0.0002), while expression of IGFBP-5, -rP2 (CTGF), -rP4 (Cyr61), FOSL1, LOXL2, OAZ1 and CDK4 was not different between groups. In line with the gene expression we found increased cell culture supernatant concentrations of IGFBP-3 (p = 0.006) in emphysema. CONCLUSION: These data support the hypothesis that premature aging of lung fibroblasts occurs in emphysema, via a telomere-independent mechanism. The upregulation of the senescence-associated IGFBP-3 and -rP1 in emphysema suggests that inhibition of the action of insulin and insulin-like growth factors could be involved in the reduced in vitro-proliferation rate
Absence of XMRV and Closely Related Viruses in Primary Prostate Cancer Tissues Used to Derive the XMRV-Infected Cell Line 22Rv1
The 22Rv1 cell line is widely used for prostate cancer research and other studies throughout the world. These cells were established from a human prostate tumor, CWR22, that was serially passaged in nude mice and selected for androgen independence. The 22Rv1 cells are known to produce high titers of xenotropic murine leukemia virus-related virus (XMRV). Recent studies suggested that XMRV was inadvertently created in the 1990's when two murine leukemia virus (MLV) genomes (pre-XMRV1 and pre-XMRV-2) recombined during passaging of the CWR22 tumor in mice. The conclusion that XMRV originated from mice and not the patient was based partly on the failure to detect XMRV in early CWR22 xenografts. While that deduction is certainly justified, we examined the possibility that a closely related virus could have been present in primary tumor tissue. Here we report that we have located the original prostate tumor tissue excised from patient CWR22 and have assayed the corresponding DNA by PCR and the tissue sections by fluorescence in situ hybridization for the presence of XMRV or a similar virus. The primary tumor tissues lacked mouse DNA as determined by PCR for intracisternal A type particle DNA, thus avoiding one of the limitations of studying xenografts. We show that neither XMRV nor a closely related virus was present in primary prostate tissue of patient CWR22. Our findings confirm and reinforce the conclusion that XMRV is a recombinant laboratory-generated mouse virus that is highly adapted for human prostate cancer cells
Prevalence of Hepatitis E Virus in Swine Fed on Kitchen Residue
The aim of this study was to investigate the prevalence of swine hepatitis E virus (HEV) in pigs fed different feedstuffs (kitchen residue or mixed feeds) and genetic identification of HEV isolated in Hebei province, China. Serum and fecal samples were collected from adult swine. Anti-HEV antibody was evaluated by double sandwich antigen enzyme immunoassay. HEV RNA was extracted from fecal samples and amplified by nested RT-PCR. The reaction products were sequenced, and the sequence analyzed. Virus-like particles were distinguishable by negative staining in the electron microscope. Histopathological observation and immunohistochemical localization were used in the animal models. Overall, the anti-HEV positive percentage of serum samples from pigs fed on kitchen residue was 87.10% (27/31), and 53.06% (130/245) from pigs fed on complete feed. The HEV RNA positivity rate of fecal samples from pigs fed on kitchen residue was 61.54% (8/13), but zero for pigs fed on complete feed. Sequence analysis of these eight samples and comparison with the published sequence showed that there were eight groups that belonged to genotype 4 d and the nucleotide identity was 95.6–99.3%. swHE11 is most closely related to strain CCC220, and the other seven HEV isolates were most closely related to strains swGX40, SwCH189 and V0008ORF3, which are isolates from human and pigs. Histopathological observation showed that there was liver damage in the experimental group, and immunohistochemistry indicated that the HEV antigens were strongly positive at 7 days after infection. The results demonstrated that the prevalence of HEV in pigs fed on kitchen residue was higher than in those fed on complete feed (P<0.05)
Genetic Assignment Methods for Gaining Insight into the Management of Infectious Disease by Understanding Pathogen, Vector, and Host Movement
For many pathogens with environmental stages, or those carried by vectors or intermediate hosts, disease transmission is strongly influenced by pathogen, host, and vector movements across complex landscapes, and thus quantitative measures of movement rate and direction can reveal new opportunities for disease management and intervention. Genetic assignment methods are a set of powerful statistical approaches useful for establishing population membership of individuals. Recent theoretical improvements allow these techniques to be used to cost-effectively estimate the magnitude and direction of key movements in infectious disease systems, revealing important ecological and environmental features that facilitate or limit transmission. Here, we review the theory, statistical framework, and molecular markers that underlie assignment methods, and we critically examine recent applications of assignment tests in infectious disease epidemiology. Research directions that capitalize on use of the techniques are discussed, focusing on key parameters needing study for improved understanding of patterns of disease
A Frameshift in CSF2RB Predominant Among Ashkenazi Jews Increases Risk for Crohn's Disease and Reduces Monocyte Signaling via GMCSF
BACKGROUND & AIMS: Crohn's disease (CD) has the highest prevalence in Ashkenazi Jewish populations. We sought to identify rare, CD-associated frameshift variants of high functional and statistical effects. METHODS: We performed exome-sequencing and array-based genotype analyses of 1477 Ashkenazi Jewish individuals with CD and 2614 Ashkenazi Jewish individuals without CD (controls). To validate our findings, we performed genotype analyses of an additional 1515 CD cases and 7052 controls for frameshift mutations in the colony stimulating factor 2 receptor beta common subunit gene (CSF2RB). Intestinal tissues and blood samples were collected from patients with CD; lamina propria leukocytes were isolated and expression of CSF2RB and GMCSF-responsive cells were defined by mass cytometry (CyTOF analysis). Variants of CSF2RB were transfected into HEK293 cells and expression and functions of gene products were compared. RESULTS: In the discovery cohort, we associated CD with a frameshift mutation in CSF2RB (P=8.52x10-4); the finding was validated in the replication cohort (combined P=3.42x10-6). Incubation of intestinal lamina propria leukocytes with GMCSF resulted in high levels of phosphorylation of STAT5 and lesser increases in phosphorylation of ERK and AKT. Cells co-transfected with full-length and mutant forms of CSF2RB had reduced pSTAT5 following stimulation with GMCSF, compared to cells transfected with control CSF2RB, indicating a dominant negative effect of the mutant gene. Monocytes from patients with CD who were heterozygous for the frameshift mutation (6% of CD cases analyzed) had reduced responses to GMCSF and markedly decreased activity of aldehyde dehydrogenase; activity of this enzyme has been associated with immune tolerance. CONCLUSIONS: In a genetic analysis of Ashkenazi Jewish individuals, we associated CD with a frameshift mutation in CSF2RB. Intestinal monocytes from carriers of this mutation had reduced responses to GMCSF, providing an additional mechanism for alterations to the innate immune response in individuals with CD
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