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2022 ◽  
Vol 369 ◽  
pp. 106533
Author(s):  
Daniel T. Brennan ◽  
Paul K. Link ◽  
Zheng-Xiang Li ◽  
Laure Martin ◽  
Tim Johnson ◽  
...  

Marine Policy ◽  
2022 ◽  
Vol 137 ◽  
pp. 104874
Author(s):  
Matthew J. Spaniol ◽  
Nicholas J. Rowland

2022 ◽  
Author(s):  
Simon Young

Comprising three parts, this book is a companion volume to The Boggart: Folklore, History, Place-Names and Dialect. Part one, ‘Boggart Ephemera’, is a selection of about 40,000 words of nineteenth-century boggart writing (particularly material that is difficult to find in libraries). Part two presents a catalogue of ‘Boggart Names’ (place-names and personal names, totalling over 10,000 words). Finally, part three contains the entire ‘Boggart Census’ – a compendium of ground-breaking grassroots research. This census includes more than a thousand responses, totalling some 80,000 words, from older respondents in the north-west of England, to the question: ‘What is a boggart?’ The Boggart Sourcebook will be of interest to folklorists, historians and dialect scholars. It provides the three corpora on which the innovative monograph, The Boggart, is based.


2022 ◽  
Author(s):  
Kristoffer Marslev

Based on a Marxist reworking of the global value chains (GVC) framework, supplemented by insights from structuralist development economics and dependency theory, the thesis investigates what role evolving class relations play in processes of social and economic upgrading in global garment value chains. Situating workers’ agency at the intersection of a horizontal axis (local capital-labor-state relations) and a vertical axis (governance and distributional dynamics of the GVC), the thesis starts out by examining the key features of the 21st century garment GVC and their implications for producer countries. It is shown how a series of interrelated processes, including the transition to neoliberalism in the North, and the phase-out of quotas in the South, combined to produce a “supplier squeeze” in the garment GVC, with a simultaneous depression of export prices and an escalation of non-price requirements. Drawing on the work of the dependentista Marini, it is argued that these distributional dynamics amount to a form of unequal exchange that incentivizes manufacturers to super-exploit workers, pushing their wages below reproduction costs and/or working them beyond exhaustion.


2022 ◽  
Vol 2022 ◽  
pp. 1-8
Author(s):  
Amr Abozeid ◽  
Rayan Alanazi ◽  
Ahmed Elhadad ◽  
Ahmed I. Taloba ◽  
Rasha M. Abd El-Aziz

Since the Pre-Roman era, olive trees have a significant economic and cultural value. In 2019, the Al-Jouf region, in the north of the Kingdom of Saudi Arabia, gained a global presence by entering the Guinness World Records, with the largest number of olive trees in the world. Olive tree detecting and counting from a given satellite image are a significant and difficult computer vision problem. Because olive farms are spread out over a large area, manually counting the trees is impossible. Moreover, accurate automatic detection and counting of olive trees in satellite images have many challenges such as scale variations, weather changes, perspective distortions, and orientation changes. Another problem is the lack of a standard database of olive trees available for deep learning applications. To address these problems, we first build a large-scale olive dataset dedicated to deep learning research and applications. The dataset consists of 230 RGB images collected over the territory of Al-Jouf, KSA. We then propose an efficient deep learning model (SwinTUnet) for detecting and counting olive trees from satellite imagery. The proposed SwinTUnet is a Unet-like network which consists of an encoder, a decoder, and skip connections. Swin Transformer block is the fundamental unit of SwinTUnet to learn local and global semantic information. The results of an experimental study on the proposed dataset show that the SwinTUnet model outperforms the related studies in terms of overall detection with a 0.94% estimation error.


MAUSAM ◽  
2022 ◽  
Vol 73 (1) ◽  
pp. 1-18
Author(s):  
Y.E.A. RAJ ◽  
B. AMUDHA

The diurnal variation of north east monsoon rainfall of coastal Tamil Nadu represented by four coastal stations Chennai Nungambakkam (Nbk), Chennai Meenambakkam (Mbk), Nagapattinam (Npt) and Pamban (Pbn)  was  studied in detail based on hourly rainfall data of rainy days only, for the period 1 Oct-31 Dec for the 47/48  year period 1969-2016/2017.  Mean Octet rainfall and its anomaly were computed for the 8 octets  00-03,…., 21-24 hrs of the day and the anomaly was tested for statistical significance. Various analysis for the individual months of Oct, Nov, Dec and the entire period Oct-Dec were separately conducted.  The basic technique of evolutionary histogram analysis supplemented by harmonic analysis of octet mean rainfall anomaly was used to detect the diurnal cycle signal. Two indices  named as  diurnal variation of  rainfall index and coefficient of mean absolute octet rainfall anomaly representing the intensity of diurnal variation  in dimensionless numbers were defined,  computed  and interpreted. The analysis based on the above techniques revealed that the diurnal signal which shows an early morning maximum and late afternoon minimum of octet rainfall is well defined in Oct, decreases in Nov and further decreases in Dec for all the 4 stations. Though the diurnal variation manifests a well defined pattern in Dec the signal is not statistically significant in most cases. For Nbk and Mbk there is a weak secondary peak of octet rainfall anomaly occurring in the forenoon and afternoon respectively in Oct and Dec suggesting the presence of semi-diurnal variation of rainfall. Stationwise, the diurnal signal is most well defined for each month/season in Pbn followed by Npt, Nbk and then Mbk.   The physical causes behind the diurnal signal and its decrease as the north east monsoon season advances from Oct to Dec have been deliberated. The well known feature of nocturnal maximum of oceanic convection influencing a coastal station with maritime climate and the higher saturation at the lower levels of the upper atmosphere in the early morning hours have been advanced as some of the causes. For the much more complex feature of decrease of diurnal signal with the  advancement of the season, the decrease of minimum surface temperature over coastal Tamil Nadu from Oct to Dec causing an early morning conceptual land breeze has been shown as one of the plausible causes  based on analysis of temperature and wind.  Scope for further work based on data from automatic weather stations, weather satellites and Doppler Weather Radars has been discussed.


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