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| 2. |
- Bhattacharya, Manojit, et al.
(author)
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ChatGPT's scorecard after the performance in a series of tests conducted at the multi-country level : A pattern of responses of generative artificial intelligence or large language models
- 2024
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In: Current Research in Biotechnology. - : Elsevier BV. - 2590-2628. ; 7
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Journal article (peer-reviewed)abstract
- Recently, researchers have shown concern about the ChatGPT-derived answers. Here, we conducted a series of tests using ChatGPT by individual researcher at multi-country level to understand the pattern of its answer accuracy, reproducibility, answer length, plagiarism, and in-depth using two questionnaires (the first set with 15 MCQs and the second 15 KBQ). Among 15 MCQ-generated answers, 13 +/- 70 were correct (Median : 82.5; Coefficient variance : 4.85), 3 +/- 0.77 were incorrect (Median: 3, Coefficient variance: 25.81), and 1 to 10 were reproducible, and 11 to 15 were not. Among 15 KBQ, the length of each question (in words) is about 294.5 +/- 97.60 (mean range varies from 138.7 to 438.09), and the mean similarity index (in words) is about 29.53 +/- 11.40 (Coefficient variance: 38.62) for each question. The statistical models were also developed using analyzed parameters of answers. The study shows a pattern of ChatGPT-derive answers with correctness and incorrectness and urges for an error-free, next-generation LLM to avoid users' misguidance.
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| 3. |
- Bhowmick, S., et al.
(author)
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Saliva as a biomarker of arsenic exposure
- 2014
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In: One Century of the Discovery of Arsenicosis in Latin America (1914-2014). - : CRC Press. - 9781138001411 ; , s. 540-542
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Conference paper (peer-reviewed)abstract
- Saliva is a biofluid that has not been used extensively as a biomonitoring tool in epidemiological studies. This study presents the arsenic (As) concentrations in saliva samples collected from populations of West Bengal, India. We found a significant (p < 0.05) association between the Log transformed Daily Ingestion of As (μg day-1) and the As concentration in saliva (r = 0.68). Additionally, As concentration of saliva and urine also had a significant positive correlation (r = 0.60, p < 0.05). Male participants, smokers and cases of skin lesion were independently and significantly associated with increase in salivary As. Thus our findings show that saliva is a useful biomarker of As exposure in the study population.
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| 4. |
- Chatterjee, Sanjukta, et al.
(author)
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Mechanical reinforcement and thermal conductivity in expanded graphene nanoplatelets reinforced epoxy composites
- 2012
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In: Chemical Physics Letters. - : Elsevier BV. - 0009-2614 .- 1873-4448. ; 531, s. 6-10
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Journal article (peer-reviewed)abstract
- Influence of reinforcements on mechanical and thermal properties of graphene nanoplatelets/epoxy composites is investigated. Amine functionalized expanded graphene nanoplatelets (EGNPs) were dispersed within epoxy resins using high-pressure processor followed by three roll milling. Functionality on the EGNPs was confirmed with FTIR and micro-Raman spectroscopy. Bending and nano-mechanical testing was performed on the composites. Incorporation of EGNPs improved the flexural modulus and hardness of the composite and increased fracture toughness by up to 60%. Marked improvement was observed in thermal conductivity of the composites reaching 36% at 2 wt.% loading. Functionalized EGNPs exhibited significant improvements indicating favorable interaction at EGNPs/polymer interface.
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| 5. |
- Halder, Dipti, et al.
(author)
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Assessment of arsenic exposure risk from drinking water and dietary component in West Bengal, India
- 2013
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Conference paper (peer-reviewed)abstract
- The current status of arsenic (As) exposure risk from drinking water and different dietary components in rural Bengal has been compared in the present study. This study shows that the consumption of rice is the major source of dietary intake of inorganic As among the population when they are drinking As safe water. Consumption of vegetables does not pose a significant health threat to the population independently; it nevertheless can increase the total daily intake of inorganic As (TDI-iAs). The results indicate that when people are drinking water with As concentration <10 μg L-1, in 35% of the cases the total daily intake of inorganic As (TDI-iAs) exceeds the previous provisional tolerable daily intake (PTDI) value of 2.1 μg day-1 kg-1 BW, recommended by World Health Organization (WHO). It should be mention here that the joint FAO/WHO expert committee on food additives (JECFA) has withdrawn the previous PTDI value in their 72nd meeting because PTDI value was in the lower range of bench mark dose level for 0.5% increased of lung cancer. However, Codex Committee on Contaminants in Foods (CCCF) has argued that TDI-iAs below BMDL0.5 does not indicates that there is no risk and this motivated us to compare TDI-iAs of the participants with the previous PTDI value of 2.1 μg day-1 kg-1 bw. At the As concentration level <10 μg L-1in drinking water, the consumption of rice is the major source of daily intake of inorganic As. When As concentration in drinking water exceeds 10 μg L-1, drinking water and rice consumption contributes almost equally (~40% from rice, ~50% from drinking water, and 10% from vegetables according to median DI-iAs) and TDI-iAs exceeds previous PTDI for all the participants. The relative contribution of daily intake of iAs from drinking water (DI-iAs-DW) largely predominates over daily intake of iAs from rice (DI-iAs-R) when As concentration in drinking water exceeds 50 μg L-1. This study implies that when consumption of rice contributes significantly to the TDI-iAs, supply of drinking water to the population considering national drinking water standard of India and Bangladesh as a safety measure for As might compound the As exposure largely by increasing TDI-iAs. Thus it can be concluded that any effort to mitigate the As poisoning of rural villagers in Bengal must look beyond the drinking water and consider all the routes of exposure.
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| 6. |
- Halder, Dipti, et al.
(author)
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Risk of arsenic exposure from drinking water and dietary components : Implications for risk management in rural Bengal
- 2013
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In: Environmental Science and Technology. - : American Chemical Society (ACS). - 0013-936X .- 1520-5851. ; 47:2, s. 1120-1127
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Journal article (peer-reviewed)abstract
- This study investigates the risk of arsenic (As) exposure to the communities in rural Bengal, even when they have been supplied with As safe drinking water. The estimates of exposure via dietary and drinking water routes show that, when people are consuming water with an As concentration of less than 10 μg L-1, the total daily intake of inorganic As (TDI-iAs) exceeds the previous provisional tolerable daily intake (PTDI) value of 2.1 μg day-1 kg-1 BW, recommended by the World Health Organization (WHO) in 35% of the cases due to consumption of rice. When the level of As concentration in drinking water is above 10 μg L-1, the TDI-iAs exceeds the previous PTDI for all the participants. These results imply that, when rice consumption is a significant contributor to the TDI-iAs, supplying water with an As concentration at the current national drinking water standard for India and Bangladesh would place many people above the safety threshold of PTDI. We also found that the consumption of vegetables in rural Bengal does not pose a significant health threat to the population independently. This study suggests that any effort to mitigate the As exposure of the villagers in Bengal must consider the risk of As exposure from rice consumption together with drinking water.
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| 7. |
- Liu, Dong, et al.
(author)
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alpha Belief Propagation as Fully Factorized Approximation
- 2019
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In: 2019 7TH IEEE GLOBAL CONFERENCE ON SIGNAL AND INFORMATION PROCESSING (IEEE GLOBALSIP). - : Institute of Electrical and Electronics Engineers (IEEE).
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Conference paper (peer-reviewed)abstract
- Belief propagation (BP) can do exact inference in loop-free graphs, but its performance could be poor in graphs with loops, and the understanding of its solution is limited. This work gives an interpretable belief propagation rule that is actually minimization of a localized alpha-divergence. We term this algorithm as alpha belief propagation (alpha-BP). The performance of alpha-BP is tested in MAP (maximum a posterior) inference problems, where alpha-BP can outperform (loopy) BP by a significant margin even in fully-connected graphs.
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