Emotion and attribution of intentionality in leader–member relationships

In this article, we present a model of emotions and attributions of intentionality within the leader–member relationship. The model is predicated on two central ideas. The first is that leadership is intrinsically an emotional process, where leaders display emotion and attempt to evoke emotion in their members. The second is that leadership is a process of social interaction and is therefore appropriately defined in terms of social, psychological theories such as the attribution theory. Our focus is on the perspective of members, not the leaders. Specifically, members' attributions about their leader's intentions influence how the members evaluate, interpret, and eventually label the leader's influence attempts as either “true” or “pseudo” transformational leadership. These attributions are determined by and themselves influence the members' emotions. We describe each of the elements of the model and conclude with a discussion of the implications of the model for theory, research, and practice.

Spatial Technologies: What use are they to managers of environmental lands?

This paper reviews the potential use of three types of spatial technology to land managers, namely satellite imagery, satellite positioning systems and supporting computer software. Developments in remote sensing and the relative advantages of multispectral and hyperspectral images are discussed. The main challenge to the wider use of remote sensing as a land management tool is seen as uncertainty whether apparent relationships between biophysical variables and spectral reflectance are direct and causal, or artefacts of particular images. Developments in satellite positioning systems are presented in the context of land managers’ need for position estimates in situations where absolute precision may or may not be required. The role of computer software in supporting developments in spatial technology is described. Spatial technologies are seen as having matured beyond empirical applications to the stage where they are useful and reliable land management tools. In addition, computer software has become more user-friendly and this has facilitated data collection and manipulation by semi-expert as well as specialist staff.

Microsatellite instability and loss of heterozygosity at DNA mismatch repair gene loci occurs during hepatic carcinogenesis

DNA mismatch repair is an important mechanism involved in maintaining the fidelity of genomic DNA. Defective DNA mismatch repair is implicated in a variety of gastrointestinal and other turners; however, its role in hepatocellular carcinoma (HCC) has not been assessed. Formalin-fixed, paraffin-embedded archival pathology tissues from 46 primary liver tumors were studied by microdissection and microsatellite analysis of extracted DNA to assess the degree of microsatellite instability, a marker of defective mismatch repair, and to determine the extent and timing of allelic loss of two DNA mismatch repair genes, human Mut S homologue-2 (hMSH2) and human Mut L homologue-1 (hMLH1), and the tumor suppressor genes adenomatous polyposis coli gene (APC), p53, and DPC4. Microsatellite instability was detected in 16 of the tumors (34.8%). Loss of heterozygosity at microsatellites linked to the DNA mismatch repair genes, hMSH2 and/or hMLH1, was found in 9 cases (19.6%), usually in association with microsatellite instability. Importantly, the pattern of allelic loss was uniform in 8 of these 9 tumors, suggesting that clonal loss had occurred. Moreover, loss at these loci also occurred in nonmalignant tissue adjacent to 4 of these tumors, where it was associated with marked allelic heterogeneity. There was relatively infrequent loss of APC, p53, or DPC4 loci that appeared unrelated to loss of hMSH2 or hMLH1 gene loci. Loss of heterozygosity at hMSH2 and/or hMLH1 gene loci, and the associated microsatellite instability in premalignant hepatic tissues suggests a possible causal role in hepatic carcinogenesis in a subset of hepatomas.

Determination of Ralstonia (Pseudomonas) solanacearum rDNA subgroups by PCR tests

Rapid and sensitive polymerase chain reaction (PCR) methods ape described for determination of the two 16 S rDNA subgroups of Ralstonia solanacearum, the causal agent of bacterial wilt. A third subgroup consisting of Indonesian R. solanacearum isolates belonging to Division II, the blood disease bacterium and Pseudomonas syzygii can also be identified. Primers were designed to sequences within R, solanacearum 16 S rDNA (equivalent to Escherichia coli 16 S rDNA positions 74-97, 455-475, 1454-1474), and the internal transcribed spacer region between the 16 S and 23 S rDNA genes. Different combinations of forward and reverse primers allowed selective PCR amplification of (a) R. solanacearum Division I (biovars 3, 4 and 5), (b) Division TI (biovars 1, N2, and 2) including the blood disease bacterium and P. syzygii, or (c) amplification of Division II only except for five biovar 1, 2 or N2 isolates of R. solanacearum from Indonesia, P. syzygii and the BDB. A total of 104 R. solanacearum, 14 blood disease bacterium and 10 P. syzygii isolates were tested. Simultaneous detection of species and subdivision was achieved by designing a multiplex PCR test in which a 288-base pair (bp) band is produced by all R. solanacearum isolates, and an additional 409-bp band in Division I strains.

The conserved quantity theory of causation and chance raising

In this paper I offer an 'integrating account' of singular causation, where the term 'integrating' refers to the following program for analysing causation. There are two intuitions about causation, both of which face serious counterexamples when used as the basis for an analysis of causation. The 'process' intuition, which says that causes and effects are linked by concrete processes, runs into trouble with cases of misconnections', where an event which serves to prevent another fails to do so on a particular occasion and yet the two events are linked by causal processes. The chance raising intuition, according to which causes raise the chance of their effects, easily accounts for misconnections but faces the problem of chance lowering causes, a problem easily accounted for by the process approach. The integrating program attempts to provide an analysis of singular causation by synthesising the two insights, so as to solve both problems. In this paper I show that extant versions of the integrating program due to Eells, Lewis, and Menzies fail to account for the chance-lowering counterexample. I offer a new diagnosis of the chance lowering case, and use that as a basis for an integrating account of causation which does solve both cases. In doing so, I accept various assumptions of the integrating program, in particular that there are no other problems with these two approaches. As an example of the process account, I focus on the recent CQ theory of Wesley Salmon (1997).