The relationship between job satisfaction, personality and intelligence over different job positions within an organization

Töö eesmärgiks oli uurida tööga rahulolu seoseid isiksuseomaduste ja vaimse võimekusega ning seda konkreetses ühes homogeenses keskkonnas, milleks on üks kommertspank Eestis. Vaimse võimekuse osas püstitatud hüpoteesid olid, et madalama vaimse võimekusega inimesed on kõrget võimekust nõudval ametikohal vähem rahulolevad ning samuti on kõrgema vaimse võimekusega töötajad vähem rahul ametikohal, kus eelduseks on madalam võimekus. Töö toimus kahes osas, kus 2016 kevadel toimus ideaalprofiilide kaardistamine ametipositsioonide lõikes ning 2018 toimus antud ametikohtade esindajate lõplik testimine. Vaatluse all oli 9 erinevat ametikohta ning lõplikud testid saadeti 513 töötajale antud organisatsioonis, kes antud ametikohtadel töötasid 30.09.2017 seisuga. Rahulolu küsimustik oli antud töö jaoks eraldi autori poolt koostatud. Isiksuseomaduste testimiseks kasutati viiefaktorilisel mudelil baseeruvat „Short Five“ (S5) küsimustikku. Vaimsete võimete testid koosnesid maatriksülesannetest ning akadeemilise testi lühiversioonist, mis hindas verbaalset, matemaatilist ja ruumilist võimekust. Isiksusetestile ning rahulolu küsimustikule vastas seejuures 124 töötajat, maatriksülesandeid täitis 97 töötajat ning akadeemilise testi 71 töötajat. Tulemustest selgus, et tööga rahulolul antud organisatsioonis/valdkonnas on oluline seos töötajate meelekindluse ja neurootilisuse näitajatega isiksuseomaduste osas. Ideaalprofiilide kaardistamine näitas samuti, et antud valdkonnas on oluliseks eelduseks just madal neurootilisuse ja kõrge meelekindluse tase. Vaimse võimekuse osas püstitatud hüpoteesid kinnitust ei leidnud, kuid ei saanud ka neid ümber lükata lõplikult. Täiendav töö laiema ja parema valimiga on vajalik. Eelnevast tulenevalt on siiski oluline personalivalikul ning tööprotsessi kujundamisel jälgida ka psühholoogilisi protsesse ning mõjutegureid, mitte ainult tööalaseid või üldiseid teadmisi ja oskusi

Meditsiinivaldkonna uuele dekaanile

Eesti Arst 2023; 102(10):50

Isiksuseomaduste, riskikäitumise ning intuitiivse otsustamise mõju riskiotsustele raamistamise tingimustes: Kommertspanga krediidiprotsessis osalejate näitel

Töö eesmärgiks oli uurida emotsionaalse fooniga raamistamise mõju olemasolu riskiotsustele konkreetses keskkonnas, kus riskiotsuseid igapäevaselt tehakse. Valimiks oli seejuures 91 pangatöötajat (46 naist, 45 meest), kes tegelevad igapäevaselt laenuotsustega seotud info analüüsimisega ja selle baasil otsuste langetamisega. Lisaks uuriti antud töös ka võimalikke teisi mõjutegureid (isiksuseomadused ning riski vältiv käitumine), mis veel otsuse langetamist võivad mõjutada. Uuringus oli tegu sõltumatute gruppidega katseplaaniga, kus katseisikud jagati juhuslikkuse alusel kolme katsegruppi ning iga gruppi raamistati erinevalt (positiivne, neutraalne ja negatiivne taust). Otsustusülesanded ja raamid olid autori poolt koostatud ning isiksuseomaduste ja riski käitumise testimiseks kasutati SX5, IAT ning BART teste. Tulemustest selgus, et igapäevase töö iseloomule vastavate hüpoteetiliste otsustusülesannete puhul olid katseisikud raamistamisest olulisel määral mõjutatud. Positiivne raam muutis inimesed seejuures riski vältivaks, kus ebakindla ülesande puhul valiti pigem eitav vastus. Muude tegurite osas leiti statistiliselt oluline seos implitsiitse ekstravertsusega, meelekindlusega ning vanusega, mis samuti otsuste tegemist mõjutasid. Tulemustest saab järeldada, et krediidiotsuste puhul, mis eeldab küll protseduuride järgimist ning põhjalikku analüüsi on siiski võimalik, et lõplikku otsust mõjutavad ka sellised tegurid nagu isiksuseomadused ja heuristikud. Eelnevast tulenevalt on oluline personalivalikul ning tööprotsessi kujundamisel jälgida ka psühholoogilisi protsesse ning mõjutegureid, mitte ainult tööalaseid teadmisi ja oskusi.http://www.ester.ee/record=b4519826*es

Süsinikumaksuga kliima soojenemise vastu? Energiakaubanduse keskkonnakaitseliste aspektide reguleerimine WTO raamistikus

http://tartu.ester.ee/record=b2610749~S1*es

CCL5/CCR1 axis regulates multipotency of human adipose tissue derived stromal cells

AbstractSeveral potential clinical applications of stem cells rely on their capacity to migrate into sites of inflammation where they contribute to tissue regeneration processes. Inflammatory signals are partially mediated by chemokines acting via their receptors expressed on the target cells. Data concerning the repertoire and biological activities of chemokine receptors in human adipose tissue derived stromal cells (ADSCs) are limited. Here we show that CCR1 is one of the few chemokine receptors expressed in ADSCs at a high level. CCR1 expression varies in ADSCs derived from different donors. It sharply decreases in the early phase of ADSCs in vitro propagation, but further demonstrates relative stability. Expression of CCR1 positively correlates with expression of SOX2, OCT4 and NANOG, transcription factors responsible for maintenance of the stemness properties of the cells. We demonstrate that signaling via CCL5/CCR1 axis triggers migration of ADSCs, activates ERK and AKT kinases, stimulates NFκB transcriptional activity and culminates in increased proliferation of CCR1+ cells accompanied with up-regulation of SOX2, OCT4 and NANOG expression. Our data suggest that chemokine signaling via CCR1 may be involved in regulation of stemness of ADSCs

Prostaglandin D2 Receptor DP1 Antibodies Predict Vaccine-induced and Spontaneous Narcolepsy Type 1 : Large-scale Study of Antibody Profiling

AbstractBackground Neuropathological findings support an autoimmune etiology as an underlying factor for loss of orexin-producing neurons in spontaneous narcolepsy type 1 (narcolepsy with cataplexy; sNT1) as well as in Pandemrix influenza vaccine-induced narcolepsy type 1 (Pdmx-NT1). The precise molecular target or antigens for the immune response have, however, remained elusive. Methods Here we have performed a comprehensive antigenic repertoire analysis of sera using the next-generation phage display method - mimotope variation analysis (MVA). Samples from 64 children and adolescents were analyzed: 10 with Pdmx-NT1, 6 with sNT1, 16 Pandemrix-vaccinated, 16 H1N1 infected, and 16 unvaccinated healthy individuals. The diagnosis of NT1 was defined by the American Academy of Sleep Medicine international criteria of sleep disorders v3. Findings Our data showed that although the immunoprofiles toward vaccination were generally similar in study groups, there were also striking differences in immunoprofiles between sNT1 and Pdmx-NT1 groups as compared with controls. Prominent immune response was observed to a peptide epitope derived from prostaglandin D2 receptor (DP1), as well as peptides homologous to B cell lymphoma 6 protein. Further validation confirmed that these can act as true antigenic targets in discriminating NT1 diseased along with a novel epitope of hemagglutinin of H1N1 to delineate exposure to H1N1. Interpretation We propose that DP1 is a novel molecular target of autoimmune response and presents a potential diagnostic biomarker for NT1. DP1 is involved in the regulation of non-rapid eye movement (NREM) sleep and thus alterations in its functions could contribute to the disturbed sleep regulation in NT1 that warrants further studies. Together our results also show that MVA is a helpful method for finding novel peptide antigens to classify human autoimmune diseases, possibly facilitating the design of better therapies.Peer reviewe

Intrusion detection systems for smart home IoT devices: experimental comparison study

Smart homes are one of the most promising applications of the emerging Internet of Things (IoT) technology. With the growing number of IoT related devices such as smart thermostats, smart fridges, smart speaker, smart light bulbs and smart locks, smart homes promise to make our lives easier and more comfortable. However, the increased deployment of such smart devices brings an increase in potential security risks and home privacy breaches. In order to overcome such risks, Intrusion Detection Systems are presented as pertinent tools that can provide network-level protection for smart devices deployed in home environments. These systems monitor the network activities of the smart home-connected de-vices and focus on alerting suspicious or malicious activity. They also can deal with detected abnormal activities by hindering the impostors in accessing the victim devices. However, the employment of such systems in the context of a smart home can be challenging due to the devices hardware limitations, which may restrict their ability to counter the existing and emerging attack vectors. Therefore, this paper proposes an experimental comparison between the widely used open-source NIDSs namely Snort, Suricata and Bro IDS to find the most appropriate one for smart homes in term of detection accuracy and resources consumption including CP and memory utilization. Experimental Results show that Suricata is the best performing NIDS for smart homesComment: 7 pages, 4 figures, 2 table

Performance comparison of intrusion detection systems and application of machine learning to Snort system

This study investigates the performance of two open source intrusion detection systems (IDSs) namely Snort and Suricata for accurately detecting the malicious traffic on computer networks. Snort and Suricata were installed on two different but identical computers and the performance was evaluated at 10 Gbps network speed. It was noted that Suricata could process a higher speed of network traffic than Snort with lower packet drop rate but it consumed higher computational resources. Snort had higher detection accuracy and was thus selected for further experiments. It was observed that the Snort triggered a high rate of false positive alarms. To solve this problem a Snort adaptive plug-in was developed. To select the best performing algorithm for Snort adaptive plug-in, an empirical study was carried out with different learning algorithms and Support Vector Machine (SVM) was selected. A hybrid version of SVM and Fuzzy logic produced a better detection accuracy. But the best result was achieved using an optimised SVM with firefly algorithm with FPR (false positive rate) as 8.6% and FNR (false negative rate) as 2.2%, which is a good result. The novelty of this work is the performance comparison of two IDSs at 10 Gbps and the application of hybrid and optimised machine learning algorithms to Snort