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Background: Chronic obstructive pulmonary disease (COPD) is the most prevalent long-term respiratory condition. Patients with COPD experience detrimental effects of COVID-19 infection. Objective: To figure out whether COPD is a risk factor influencing the progression of COVID-19 and to explore the clinical value of laboratory biomarkers to assess the severity of COVID-19 in patients with COPD comorbidity. Methods: In total, 1572 participants aged 35 to 70 years were enrolled to a tertiary hospital in Bangladesh between March 2022 and October 2022. Participants were categorized into four groups: (1) control, (2) COPD, (3) COVID-19, and (4) COVID-19 with COPD, and blood levels of clinical laboratory markers were assessed to analyze how these markers differ among the study groups. Results: COVID-19 patients with COPD had a significantly lower level of sodium (131.81 ± 2.8 mmol/L) and calcium (1.91 ± 0.28 mmol/L), and a significantly higher level of NT-proBNP (568.45 ± 207.40 pg/mL), bilirubin (1.34 ± 0.54 mg/dL), fibrinogen (577.27 ± 145.24 mg/dL), D-dimer (2.97 ± 2.25 μg/mL), C-reactive protein (71.08 ± 62.42 mg/L), interleukin-6 (166.47 ± 174.39 pg/mL), and procalcitonin (0.25 ± 0.30 ng/mL) compared to other study groups patients (p < 0.0001). In addition, the GOLD 4 group demonstrated significantly altered clinical parameters among COVID-19 patients with COPD. Furthermore, NT-proBNP, interleukin 6, D-dimer, C-reactive protein, and fibrinogen demonstrated excellent diagnostic performance in predicting disease severity among the COVID-19 patients with COPD, with a cut-off value of 511.2 pg/mL, 51.375 pg/mL, 1.645 μg/mL, 40.2 mg/L, and 510 mg/dL, respectively. Our results also indicate that inflammatory markers had significant positive correlations with the biochemical and coagulation markers in the COVID-19 patients suffering with COPD (p < 0.0001). Conclusions: NT-proBNP, interleukin 6, D-dimer, C-reactive protein, and fibrinogen are the most potential parameters for differentiating severe cases of COVID-19.

Among other motif finding algorithms Planted Motif Search (PMS) or (l, d) motif search algorithms are considered as next-generation motif finding algorithms. Here, n strings and two integer l and d are provided as input in PMS. It gives outputs of all sequences of length M in each input string, where each occurrence varies from Min at most d points. This paper proposes a new algorithm, for the (l, d) motif discovery problem in which we find all strings of length l that seems in every string of a provided set of strings with at most d mismatches has been. After proper investigation of the PMS problem, it has been shown that this is an NP-hard exact algorithm. Usually, in the worst-case scenarios, all the known exact algorithms for PMS need exponential time in some of the underlying parameters. In this paper, we proposed a faster approach that reduces the searching time in the sample-driven part of the algorithm. In particular, we used dynamic programming techniques to eliminate the recalculation of the values of some common subtree and introduced some new speedup techniques like using a linked list, reduced l-mers for making the algorithm faster. Due to the use of Linked List as a main speedup technique, we named our proposed algorithm as Linked List Implementation technique of PMS8 (LL-PMS8).

For sustainable agricultural practices, groundwater quality must be suitable for irrigation; otherwise, it can degrade soil and diminish crop production. The entropy information theory, several irrigational indices, multivariate statistics, GIS and geostatistics are used in this work to evaluate the geographical distribution and quality of groundwater in the Indian Sundarban region. 33 samples of groundwater have been collected in total, and they were evaluated for major cations, anions as well as other parameters like electrical conductivity (EC), soluble sodium percentage (SSP), potential salinity (PS), total dissolved solids (TDS), Kelly ratio (KR), Sodium absorption ratio (SAR), permeability index (PI), residual sodium carbonate (RSC), Magnesium Hazard (MH) and residual sodium bicarbonate (RSBC). The overall trend of the principal cations and anions is in the sequence of Na+ ≥ Mg2+ ≥ Ca2+ ≥ K2+ and HCO3− ≥ Cl− ≥ NO3− ≥ SO42− ≥ F−, respectively, whereas the spatial variation of %Na, SAR, RSBC, and MH demonstrate very poor irrigation water quality, and spatial variation of KR, RSC, SSP, PI, and PS signifies that the irrigation water quality is excellent to good. The hydrochemical facies indicates that mixed type makes up the bulk (51.51%) of the water samples. Following the Wilcox plot, more than 75% of the water samples are good to doubtful; however, by the US salinity hazard map, roughly 60.60% of the samples had high salinity (C3-S1 zone). As per the entropy-weighted water quality index for irrigation (EWQII), 60.60% of samples possess good to average quality, while the remaining 39.40% (poor) require severe restrictions before use in agricultural operations. As a result, to assure sustainable agricultural development, in the research area, continuous monitoring and water resource management are required.