Il-forma ortografika u t-tifsira semantika fl-għażla tal-lessiku Malti fl-oqsma tat-traduzzjoni u tat-terminoloġija

Din l-analiżi turi kif is-Semitiku, ir-Rumanz u l-Ingliż li minnhom magħmul il-Malti jippermettu dinamiżmu u flessibilità kbira fil-qasam tat-traduzzjoni kemm letterarja kif ukoll nonletterarja. Il-forma ortografika u t-tifsira semantika tal-kliem Malti-Rumanz huma ħafna drabi l-istess bħal dawk tal-kliem Malti-Ingliż u dan għax kemm l-Ingliż kif ukoll it-Taljan għandhom fil-lessiku għadd ta’ għeruq komuni li etimoloġikament imorru lura għal-Latin Medjevali. Ir-rwol tat-traduzzjoni hu li jwassal it-test sors b’mod awtentiku lillqarrej tat-test mira u mhux li jippreserva l-element Semitiku fil-Malti. Għalhekk għandha ssir distinzjoni bejn lingwa u traduzzjoni sabiex jiġi osservat id-determiniżmu lingwisitku stabbilit mill-awtur tal-lingwa sors fl-għażla tal-lessiku li twassal għar-replika vera tat-test oriġinali fil-lingwa mira tat-traduttur.peer-reviewe

The effect of mark enhancement techniques on the presumptive and confirmatory tests for blood

An investigation into the effects of physical and chemical enhancement on subsequent presumptive and confirmatory tests for human blood is presented. Human blood was deposited onto porous (white 80gsm paper and brown envelope) and non-porous (tile and linoleum) substrates in a depletion series (30 depletions on non-porous and 20 on porous) and subjected to three ageing periods; 1, 7 and 28 days. A number of enhancement techniques were tested [fluorescence, black magnetic powder (BMP), iron-oxide black powder suspension (PS), cyanoacrylate (CA) fuming, acid violet 17 (AV17), acid yellow 7 (AY7), ninhydrin, DFO and Bluestar Forensic Magnum (BFM) luminol] to evaluate their potential effects on subsequent presumptive and confirmatory tests. AV17 and Bluestar provided the best enhancement and fully enhanced all depletions in the series. The sensitivity of the Kastle-Meyer (KM) (presumptive), Takayama and RSID-Blood tests (confirmatory) was initially investigated to determine the range of detectable depletions. The KM test detected all depletions, whereas the Takayama test detected up to depletion 6 and RSID-Blood detected up to depletion 20 (paper), 10 (envelope), 15 (tile) and 9 (lino). The abilities of these tests to detect blood after enhancement were then observed.A number of techniques resulted in little to no effect on any of the blood tests, whereas adverse effects were observed for others. Ninhydrin and CA fuming caused weak but instantaneous positive KM results whereas methanol-based AV17 and AY7 delayed the reaction by as much as 1 min. The Takayama test was not very sensitive, therefore, its performance was easily affected by enhancement and negative results were often observed. RSID-Blood tests were largely unaffected by chemical enhancement although a drop in positive results was observed for some of the techniques when compared to positive controls.Using a standard procedure for DNA extraction, all the tested blood samples (before and after enhancement) gave a detectable quantity of DNA and were successfully profiled. Out of the 45 samples processed for DNA profiling, 44 gave full profiles, while the remaining showed allele drop out in one or two loci

Impact of strain on the excitonic linewidth in transition metal dichalcogenides

Monolayer transition metal dichalcogenides (TMDs) are known to be highly sensitive to externally applied tensile or compressive strain. In particular, strain can be exploited as a tool to control the optical response of TMDs. However, the role of excitonic effects under strain has not been fully understood yet. Utilizing the strain-induced modification of electron and phonon dispersion obtained by first principle calculations, we present in this work microscopic insights into the strain-dependent optical response of various TMD materials. In particular, we explain recent experiments on the change of excitonic linewidths in strained TMDs and predict their behavior for tensile and compressive strain at low temperatures.Comment: 7 pages, 7 figure

Machine Learning Challenges of Biological Factors in Insect Image Data

The BIOSCAN project, led by the International Barcode of Life Consortium, seeks to study changes in biodiversity on a global scale. One component of the project is focused on studying the species interaction and dynamics of all insects. In addition to genetically barcoding insects, over 1.5 million images per year will be collected, each needing taxonomic classification. With the immense volume of incoming images, relying solely on expert taxonomists to label the images would be impossible; however, artificial intelligence and computer vision technology may offer a viable high-throughput solution. Additional tasks including manually weighing individual insects to determine biomass, remain tedious and costly. Here again, computer vision may offer an efficient and compelling alternative. While the use of computer vision methods is appealing for addressing these problems, significant challenges resulting from biological factors present themselves. These challenges are formulated in the context of machine learning in this paper.Comment: 4 pages, 3 figures. Submitted to the Journal of Computational Vision and Imaging System

Protecting informative messages over burst error channels in chain-based wireless sensor networks

Regardless of the application, the way that data and information are disseminated is an important aspect in Wireless Sensor Networks (WSNs). The wireless data dissemination protocol should often guarantee a minimum reliability requirement. In this regard and to well-balance the energy and reliability, the more important packets should be protected by more powerful error control codes than the less important ones. This information-aware capability allows a system to deliver critical information with high reliability but potentially at a higher resource cost. In this paper, we first find and evaluate the factors that may influence the importance level of a packet and then design an error control approach by adaptively selecting codes for each individual links which experience long-term-fading and for each individual packet at run-time instead of applying network-wide settings prior to deployment. Moreover, we target the poor-explored chain-based topology that is of interest for many applications (e.g. monitoring bridge, tunnel, etc.). Simulation results validate the superiority of our approach compared with a number of Reed-Solomon-based error control approaches

An Empirical Examination of the Correlates of Perceptions of Company Politics*

Shaker A. Zahra is an Assistant Professor of Management and Paul J. Champagne is an Associate Professor of Management in the School of Business Administration at Old Dominion University

A Data Annotation Architecture for Semantic Applications in Virtualized Wireless Sensor Networks

Wireless Sensor Networks (WSNs) have become very popular and are being used in many application domains (e.g. smart cities, security, gaming and agriculture). Virtualized WSNs allow the same WSN to be shared by multiple applications. Semantic applications are situation-aware and can potentially play a critical role in virtualized WSNs. However, provisioning them in such settings remains a challenge. The key reason is that semantic applications provisioning mandates data annotation. Unfortunately it is no easy task to annotate data collected in virtualized WSNs. This paper proposes a data annotation architecture for semantic applications in virtualized heterogeneous WSNs. The architecture uses overlays as the cornerstone, and we have built a prototype in the cloud environment using Google App Engine. The early performance measurements are also presented.Comment: This paper has been accepted for presentation in main technical session of 14th IFIP/IEEE Symposium on Integrated Network and Service Management (IM 2015) to be held on 11-15 May, 2015, Ottawa, Canad

A trust-based probabilistic coverage algorithm for wireless sensor networks

Sensing coverage is a fundamental issue for many applications in wireless sensor networks. Due to sensors resource limitations, inherent uncertainties associated with their measurements, and the harsh and dynamic environment in which they are deployed, having a QoS-aware coverage scheme is a must. In this paper, we propose a Trust-based Probabilistic Coverage algorithm, which leverages the trust concept to tackle the uncertainties introduced by the nodes and the environment, in which they operate. We formulate this problem as an Integer Linear Programming (ILP) problem, which is able to always guarantee the required QoS despite uncertainties introduced by node and/or environment. In consideration of the limitation of ILP, we also put forward a greedy heuristic algorithm to achieve almost the same ILP results without suffering from complexities imposed by ILP. We examine our heuristic with different input parameters and compare it with the ILP approach. Simulation results are presented to verify our approaches