254 research outputs found
Alien Registration- Cahill, Edward (Portland, Cumberland County)
https://digitalmaine.com/alien_docs/25222/thumbnail.jp
Historical Lights from Judicial Decisions
The history of a nation is to be looked for in a great variety of places. Its traditions, its public and private records, its religious and social orders, its literature and its laws, each yield copious results to the researches of the historian. The social, religious and economic conditions of a nation at any period of its history, the state of theĀ· domestic relations, the rights of property and of succession, the growth of personal liberty, all these and many more find their accurate expression sooner or later, in the written or unwritten laws of the land. And the movement of society, whether it be forward or backward, wilt there be indicated. The savage needs few laws, and such as he has are elementary and as unstable as the wll of a tyrant ruler. The nomad must have laws to protect his flocks and herds, and his possessary rights of pasturage, and he needs little more. The agriculturist requires, forĀ·his protection, more complicated land laws, and the advent of trade, navigation and manufacturing have been marked by the appearance of laws for their protection. To speak inversely toĀ·the fact, when laws for the protection of these interests are found, the existence of such interests may be conclusively inferred
Wide-coverage deep statistical parsing using automatic dependency structure annotation
A number of researchers (Lin 1995; Carroll, Briscoe, and Sanfilippo 1998; Carroll et al. 2002; Clark and Hockenmaier 2002; King et al. 2003; Preiss 2003; Kaplan et al. 2004;Miyao and Tsujii 2004) have convincingly argued for the use of dependency (rather than CFG-tree) representations
for parser evaluation. Preiss (2003) and Kaplan et al. (2004) conducted a number of experiments comparing ādeepā hand-crafted wide-coverage with āshallowā treebank- and machine-learning based parsers at the level of dependencies, using simple and automatic methods to convert tree output generated by the shallow parsers into dependencies. In this article, we revisit the experiments
in Preiss (2003) and Kaplan et al. (2004), this time using the sophisticated automatic LFG f-structure annotation methodologies of Cahill et al. (2002b, 2004) and Burke (2006), with surprising results. We compare various PCFG and history-based parsers (based on Collins, 1999; Charniak, 2000; Bikel, 2002) to find a baseline parsing system that fits best into our automatic dependency structure annotation technique. This combined system of syntactic parser and dependency structure annotation is compared to two hand-crafted, deep constraint-based parsers (Carroll and Briscoe 2002; Riezler et al. 2002). We evaluate using dependency-based gold standards (DCU 105, PARC 700, CBS 500 and dependencies for WSJ Section 22) and use the Approximate Randomization Test (Noreen 1989) to test the statistical significance of the results. Our experiments show that machine-learning-based shallow grammars augmented with sophisticated automatic dependency annotation technology outperform hand-crafted, deep, widecoverage constraint grammars. Currently our best system achieves an f-score of 82.73% against the PARC 700 Dependency Bank (King et al. 2003), a statistically significant improvement of 2.18%over the most recent results of 80.55%for the hand-crafted LFG grammar and XLE parsing system of Riezler et al. (2002), and an f-score of 80.23% against the CBS 500 Dependency Bank (Carroll, Briscoe, and Sanfilippo 1998), a statistically significant 3.66% improvement over the 76.57% achieved by the hand-crafted RASP grammar and parsing system of Carroll and
Briscoe (2002)
Not a melting pot: Plant species aggregate in their non-native range
Aim Plant species continue to be moved outside of their native range by human activities. Here, we aim to determine whether, once introduced, plants assimilate into native communities or whether they aggregate, thus forming mosaics of native- and alien-rich communities. Alien species might aggregate in their non-native range owing to shared habitat preferences, such as their tendency to establish in high-biomass, species-poor areas. Location Twenty-two herbaceous grasslands in 14 countries, mainly in the temperate zone. Time period 2012-2016. Major taxa studied Plants. Methods We used a globally coordinated survey. Within this survey, we found 46 plant species, predominantly from Eurasia, for which we had co-occurrence data in their native and non-native ranges. We tested for differences in co-occurrence patterns of 46 species between their native (home) and non-native (away) range. We also tested whether species had similar habitat preferences, by testing for differences in total biomass and species richness of the patches that species occupy in their native and non-native ranges. Results We found the same species to show different patterns of association depending on whether they were in their native or non-native range. Alien species were negatively associated with native species; instead, they aggregated with other alien species in species-poor, high-biomass communities in their non-native range compared with their native range. Main conclusions The strong differences between the native (home) and non-native (away) range in species co-occurrence patterns are evidence that the way in which species associate with resident communities in their non-native range is not species dependent, but is instead a property of being away from their native range. These results thus highlight that species might undergo important ecological changes when introduced away from their native range. Overall, we show origin-dependent associations that result in novel communities, in which alien-rich patches exist within a mosaic of native-dominated communities
Chatbots to Support Mental Health & Wellbeing:Early Findings from ChatPal Use During COVID-19 Lockdown
Short-Term Overfeeding Increases Circulating Adiponectin Independent of Obesity Status
Background: Adiponectin is an adipose tissue derived hormone which strengthens insulin sensitivity. However, there is little data available regarding the influence of a positive energy challenge (PEC) on circulating adiponectin and the role of obesity status on this response.
Objective: The purpose of this study was to investigate how circulating adiponectin will respond to a short-term PEC and
whether or not this response will differ among normal-weight(NW), overweight(OW) and obese(OB).
Design: We examined adiponectin among 64 young men (19-29 yr) before and after a 7-day overfeeding (70% above
normal energy requirements). The relationship between adiponectin and obesity related phenotypes including; weight, percent body fat (%BF), percent trunk fat (%TF), percent android fat (%AF), body mass index (BMI), total cholesterol, HDLc, LDLc, glucose, insulin, homeostatic model assessment insulin resistance (HOMA-IR) and b-cell function (HOMA-b) were analyzed before and after overfeeding.
Results: Analysis of variance (ANOVA) and partial correlations were used to compute the effect of overfeeding on adiponectin and its association with adiposity measurements, respectively. Circulating Adiponectin levels significantly increased after the 7-day overfeeding in all three adiposity groups. Moreover, adiponectin at baseline was not significantly different among NW, OW and OB subjects defined by either %BF or BMI. Baseline adiponectin was negatively correlated with weight and BMI for the entire cohort and %TF, glucose, insulin and HOMA-IR in OB. However, after controlling for insulin resistance the correlation of adiponectin with weight, BMI and %TF were nullified.
Conclusion: Our study provides evidence that the protective response of adiponectin is preserved during a PEC regardless
of adiposity. Baseline adiponectin level is not directly associated with obesity status and weight gain in response to shortterm overfeeding. However, the significant increase of adiponectin in response to overfeeding indicates the physiological potential for adiponectin to attenuate insulin resistance during the development of obesity
Insights and lessons learned from trialling a mental health chatbot in the wild
This study reports on the development and 'in the wild' trialling of a chatbot (ChatPal) which promotes good mental wellbeing. A stakeholder-centered approach for design was adopted where end users, mental health professionals and service users were involved in the design which was centered around positive psychology. In the wild usage of the chatbot was investigated from Jul-20-Mar-21. Exploratory analyses of usage metrics were carried out using the event log data. User tenure, unique usage days, total chatbot interactions and average daily interactions were used in K-means clustering to identify user archetypes. The chatbot was used by a variety of age groups (18-65+) and genders, mainly those living in Ireland. K-means clustering identified three clusters: sporadic users (n=4), frequent transient users (n=38) and abandoning users (n=169) each with distinct usage characteristics. This study highlights the importance of event log data analysis for making improvements to the mental health chatbot.</p
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