Table 51 Sample Clauses

Table 51. Pest studied in the Use Case of FARSALA for the cultivation of cotton 45 Table 52. Pests studied in the Use Case of Use Case of PELLA for the cultivation of peach. 45 Table 53. Xxxx studied in the Use Case of KASTORIA for the cultivation of table tomato. 45 Table 54. Xxxx studied in the Use Case of MESSINIA for the cultivation of olives. 45 Table 55. Pest studied in the Use Case of XXXXXXXX for the cultivation of vine. 46 Table 56. Pests studied in the Use Case of CONFAGRI for the cultivation of olives. 46 Definitions, Acronyms and Abbreviations Acronym Title AB Advisory Board ALs Action Leaders AUTH ARISTOTELIO PANEPISTIMIO THESSALONIKIS (Aristotle University of Thessaloniki – Special Account of Research Funds) CE Circular Economy EU European Union GAIA GAIA EPICHEIREIN ANONYMI ETAIREIA PSIFIAKON YPIRESION NP NEUROPUBLIC AE PLIROFORIKIS & EPIKOINONION SF Smart Farming ORESTIADA Enosi Agrotikon Synetairismon Orestiadas VELVENTOS Agrotikos Synetairismos Epexergasias kai Poliseos Oporokipeftikon Proionton (ASEPOP) Velventou SYN.P.E AIGINA Omada Pagagogon Kelyfotou Fistikiou Aiginas ELASSONA Agrotikos Synetairismos Fytikis kai Zoikis Paragogis – Xxxxx Xxxxxxxxx LASITHI Enosi Agrotikon Synetairismon Oropediou Lasithiou SPEKO-XXXXX Koinopraksia Agrotikon Synetairismon – SPEKO-XXXXX KIATO Geoponiki Kiatou STYLIDA Stylis Olive Producers Cooperative THESTO Agricultural Cooperative of Xxxxxxxxxx Xxxxxx Producers THESGI Farmers’ Cooperative of Thessaly XXXXXXXXX Agricultural Cooperative Partnership Xxxxxxxxx Union X.X. XXXXXXXX Xxxx Xxxxxxxx SCG CONFAGRI Confederação Nacional das Cooperativas Agrícolas e do Crédito Agrícola de Portugal CCRL MESSINIA Agrotikos Sineterismos Messinias “Enosi Messinias” XXXX Xxxxxxxxxxx ΑE FARSALA Agrotikos Synetairismos “Farsalon Gis” EUBOEA Atypi Omada Paragogon Tomatas Dystou PELLA NOVAPLAN IKE KOMOTINI Thrakika Ekokkistiria DRAMA Enosi Agrotikon Synetairismon Dramas
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Table 51. Pest studied in the Use Case of FARSALA for the cultivation of cotton. FARSALA - cotton 1 Pectinophora gossypiella 2 Helicoverpa armigera
Table 51. The effect of Phenylalanine-Tyrosine ratio on FTT-non-dominant hand while adjusting for demographics Dependent Independent N β SE t p- value FTT-non-dominant hand Phe-Tyr ratio 71.00 20.58 32.29 0.64 0.53 Age -0.89 0.64 -1.40 0.17 Sex 16.70 18.90 0.88 0.38 Race -30.10 19.62 -1.53 0.13 Smoker -19.30 13.04 -1.48 0.14
Table 51. Summary and Resource Information Description Lists the summary and resource information of the selected virtual machine. Data displayed • Current Status. The current status of the selected virtual machine: Turned off or Powered On. • Processors. The number of CPUs used by the selected virtual machine. • Uptime. The percentage of time during which the virtual machine is running. • Memory Capacity. The amount of memory resources allocated to the selected virtual machine. • Powered on Date. The date on which the selected virtual machine is powered. • Network Interface. The number of network interface cards that exist on the selected virtual machine. • OS Reboot Date. The date when rebooting the operating system. • Storage Devices. The number of physical and logical disks associated with the virtual machine. • DNS Name. The fully qualified DNS name of the selected virtual machine. • Virtual Center. The IP address of the Virtual Center to which the virtual machine belongs. • Connection Status. The virtual machine’s connection status. • Datacenter. The name of the datacenter associated with the virtual machine. • IP Address. The IP address of the virtual machine. • Cluster. The name of the cluster associated with the virtual machine. • Vmware Tools. The name of VMware applications used to manage the virtual machine. • Resource Pool. The name of resource pools associated with the virtual machine. • OS. The name of the operating system used by the selected virtual machine. • ESX Host. The IP address of the ESX host on which the virtual machine is running. • Managed Object Reference. Identifies the virtual switch in your monitored environment. Rules‌‌ Foglight® for VMware allows you to create flexible rules that can be applied to complex, interrelated data from multiple sources within your distributed system. You can associate several different actions with a rule, configure a rule so that it does not fire repeatedly, and associate a rule with schedules to define when it should and should not be evaluated. Different types of data can be used in rules, including registry variables, raw metrics, derived metrics, and topology object properties. There are two types of rules in Foglight for VMware: simple rules and multiple-severity rules. A simple rule has a single condition, and can be in one of three states: Fire, Undefined, or Normal. A multiple-severity rule can have up to five severity levels: Undefined, Fatal, Critical, Warning, and Normal. Rule conditions are re...

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