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PROSES PENGURAIAN, PENYERAPAN KARBON DAN KEPELBAGAIAN BAKAU TANAH BENCAH SETIU, TERENGGANU, MALAYSIA
No full textRelations between morphological traits and body weight of shortbelly eel, Dysomma anguillare (Actinopterygii: Anguilliformes: Synaphobranchidae), from coastal waters of Zhoushan, East China Sea, determined by multivariate analyses
No full textThe shortbelly eel, Dysomma anguillare Barnard, 1923, is an essential component in the food chain of the marine ecosystem and plays an important role in nearshore fisheriesand biodiversity in the East China Sea. In order to provide theoretical support for fisher resource assessment and sustainable utilization of D. anguillare, an important bycatch in the offshore area of China, the relations be- tween morphological traits and body weight were investigated based on the measurement of 28 metric traits for the firsttime. The cor- relation analysis showed that 25 morphological traits were significantly(P < 0.05) correlated with the logarithm of body weight (lgX ), in which the correlation coefficientof the total length (X ) was the largest with the extremely high significance(P < 0.01). The optimum multiple regression equation of morphological traits was constructed after deleting redundant independent variables: lgX = 0.367 + 0.003X + 0.010X ? 0.010X + 0.011X + 0.042X + 0.006X + 0.024X ? 0.004X . The total length (X ) had the highest positive direct relation with lgX (0.699), which was in accordance with the results of determinate coefficientanalysis, while the indirect effect of body height (X ) through lower jaw length (X ) to lgX was the greatest. The gray correlation analysis indicated that body length (X ) and distance from snout to dorsal finorigin (X ) were the most closely related to body weight. The comprehensive comparison showed that X , X , and X should be used as the ideal morphometric traits for measuring the body weight of D. anguillare, and the conclusions obtained from this study will provide valuable references for fisheryresource management of this commercial fishspecies
Oceanographic Research in the Thermaikos Gulf: A Review over Five Decades
No full textThe Thermaikos Gulf (TG) is a semi-enclosed, river-influenced, marine system situated
in the eastern Mediterranean Sea, sustaining both urban coastal regions and ecologically preserved
natural areas. Facing a plethora of environmental and anthropogenic pressures, the TG serves as a
critical nexus where human activities intersect with marine ecosystems. The quality and health of the
TG?s marine environment are tightly linked to the socioeconomic activities of the coastal communities
comprising approximately 1.5 million inhabitants. The main features of the TG?s environmental
dynamics and ecological status have been scrutinized by dedicated research endeavors during
the last 50 years. This review synthesizes the seminal findings of these investigations, offering
an evaluation of their contribution to research, their present collective impact, and their trajectory
toward the future. A severe deterioration of the TG?s environmental quality was detected in the
1970s and 1980s when the treatment of urban wastewater was completely absent. A steady trend
of recovery was observed after the 1990s; however, so far, the goal of a ?good environmental state?
mandated by national legislation and European directives has not been achieved. A clear reduction
in research was detected after 2010, associated with the recession of the Greek economy, following the
?golden period? for research in the TG from the mid-1990s until the late 2000s. The most important
research gaps and uncertainties are discussed, while specific targeted recommendations for the
improvement of monitoring and understanding of the physical, biochemical, and ecological state of
the gulf are provided: (i) increase in permanent observational stations (temporally and spatially);
(ii) inclusion of all major environmental parameters; (iii) monitoring of the quantity and quality of
all land-originated freshwater discharges; (iv) monitoring and management of important aspects
of the marine environment that have received minimal attention in the past (e.g., coastal erosion,
plastic pollution); (v) development of accurate prediction tools (e.g., numerical techniques) to support
first-level responders and efficient management; (vi) establishment of a supervising public entity
that would support the holistic overview and management of the entire TG. These suggestions
are directed at overcoming the existing uncertainties in the knowledge of the TG, safeguarding its
ecological integrity and its role as a crucial link to marine biodiversity and sustainability in the
Mediterranean basin
Key Innovations in Financing Nature-Based Solutions for Coastal Adaptation
No full textThe implementation of nature-based solutions (NBSs) for coastal adaptation to climate
change is limited by a well-documented lack of finance. Scholars agree that financial innovation represents
a solution to this problem, particularly due to its potential for mobilising private investments.
It remains unclear however how exactly innovative solutions address the specific barriers found in
NBS implementation and, given the distinctive local characteristics of NBSs, to what extent successful
innovations can be replicated in other locations. This study addresses this issue by reviewing the
literature and case studies of innovative financial solutions currently implemented in NBS projects,
highlighting which financial barriers these arrangements address and which contextual conditions
affect their applicability. We find that there is no ?low-hanging fruit? in upscaling finance in NBSs
through financial innovation. Innovative solutions are nevertheless expected to become more accessible
with the increase in NBS project sizes, the increased availability of data on NBS performance,
and the establishment of supportive policy frameworks. The flow of finance into NBS projects can be
further enhanced through the external support of both public (de-risking and regulation) and private
actors (financial expertise)
Blockchain-Based Cold Chain Traceability with NR-PBFT and IoV-IMS for Marine Fishery Vessels
No full textDue to limited communication, computing resources, and unstable environments, traditional
cold chain traceability systems are difficult to apply directly to marine cold chain traceability
scenarios. Motivated by these challenges, we construct an improved blockchain-based cold chain
traceability system for marine fishery vessels. Firstly, an Internet of Vessels system based on the
Iridium Satellites (IoV-IMS) is proposed for marine cold chain monitoring. Aiming at the problems of
low throughput, long transaction latency, and high communication overhead in traditional cold chain
traceability systems, based on the Practical Byzantine Fault Tolerance (PBFT) consensus algorithm,
a Node-grouped and Reputation-evaluated PBFT (NR-PBFT) is proposed to improve the reliability
and robustness of blockchain system. In NR-PBFT, an improved node grouping scheme is designed,
which introduces a consistent hashing algorithm to divide nodes into consensus and candidate sets,
reducing the number of nodes participating in the consensus process, to lower communication overhead
and transaction latency. Then, a reputation evaluation model is proposed to improve the node
selection mechanism of NR-PBFT. It enhances the enthusiasm of nodes to participate in consensus,
which considers the distance between fishery vessels, data size, and refrigeration temperature factors
of nodes to increase throughput. Finally, we carried out experiments on marine fishery vessels, and
the effectiveness of the cold chain traceability system and NR-PBFT were verified. Compared with
PBFT, the transaction latency of NR-PBFT shortened by 81.92%, the throughput increased by 84.21%,
and the communication overhead decreased by 89.4%
APPLICATION OF LOOP-MEDIATED ISOTHERMAL AMPLIFICATION FOR Edwardsiella ictaluri DETECTION IN INDONESIA ENTERIC SEPTICEMIA OF CATFISH
No full textLoop-mediated isothermal amplification (LAMP) method is useful for
rapidly detecting Edwardsiella ictalurid infection, especially enteric
septicemia of catfish (ESC). This study aims to investigate the LAMP method
for E. ictaluri detection in ESC. This research was an experimental study
using a total of 55 catfish, consisting of 5 negative controls and 50 catfish
injected intraperitoneally with 0.1 mL of E. ictaluri at a concentration of
105 CFU/mL. The kidneys of three fishes were randomly selected 6, 12, 18,
24, 30, 36, 42, 48, and 54 hours after infection with E. ictaluri. In addition,
samples were also collected on days 3, 5, and 7. Bacterial analysis was
determined by conventional biochemistry (genus and species test), wholegenome
sequencing of catfish, and LAMP amplification. All types of data
obtained in this study were analyzed by descriptive statistics to compare
infected and healthy catfish. The catfish were infected with E. ictaluri
after 12 hours of infection according to the LAMP amplification procedure
which revealed hemorrhages throughout the body, fins, protruding
eyes, necrosis, inflammation of the spleen, liver, intestine, pale gills, gut,
abdomen swelling, and tissue necrosis in the upper part of the head. It
can be concluded that the LAMP method is more effective than the PCR
method for detecting infection with E. ictaluri in catfish
Increasing Structural Diversity of the Early Growth Stages in Polynesian Pearls Reveals Biological Stress Suffered by the Grafts
No full textIn Polynesian pearls produced using Pinctada margaritifera var. Cumingii, we investigated
the structure of the early growth stages, from the nucleus surface up to the first deposition of the
black nacre characteristic of this subspecies. Despite simultaneous grafting from the same donor
oyster and similar cultivation conditions, we observed the deposition of various non-nacreous prenacre
structures. These unusual microstructures, which precede the return to black nacre, varied
from immediate deposition onto the nucleus surface to increasing delays, depending on the graft?s
position in the grafting series. Given the similar biological conditions of grafting and cultivation, we
suggest that, in line with recent data demonstrating genomic sensitivity to environmental conditions,
alterations in the graft cells produced during the increasing waiting period were transmitted to the
pearl sacs and the early growth stages of the grafted pearls
KERJA KERANGKA PENGESAN KAKISAN KAPAL YANG TEGUH MENGGUNAKAN PEMULAAN KONTUR DAN ALGORITMA KONTUR AKTIF DENGAN PEMPROSESAN SELARI
No full textMULTIMODAL FAKE NEWS DETECTION
No full textIn recent years, social media has increasingly become one of the popular ways for people to
consume news. As proliferation of fake news on social media has the negative impacts on individuals and society, automatic fake news detection has been explored by different research
communities for combating fake news. With the development of multimedia technology, there is
a phenomenon that cannot be ignored is that more and more social media news contains information with different modalities, e.g., texts, pictures and videos. The multiple information modalities show more evidence of the happening of news events and present new opportunities to
detect features in fake news. First, for multimodal fake news detection task, it is a challenge of
keeping the unique properties for each modality while fusing the relevant information between
different modalities. Second, for some news, the information fusion between different modalities
may produce the noise information which affects model?s performance. Unfortunately, existing
methods fail to handle these challenges. To address these problems, we propose a multimodal
fake news detection framework based on Crossmodal Attention Residual and Multichannel
convolutional neural Networks (CARMN). The Crossmodal Attention Residual Network (CARN)
can selectively extract the relevant information related to a target modality from another source
modality while maintaining the unique information of the target modality. The Multichannel
Convolutional neural Network (MCN) can mitigate the influence of noise information which may
be generated by crossmodal fusion component by extracting textual feature representation from
original and fused textual information simultaneously. We conduct extensive experiments on four
real-world datasets and demonstrate that the proposed model outperforms the state-of-the-art
methods and learns more discriminable feature representations
