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The aim of the present study was to assess the technological reliability of a domestic hybrid wastewater treatment installation consisting of a classic three-chambered (volume 6 m) septic tank, a vertical flow trickling bed filled with granules of a calcinated clay material (KERAMZYT), a special wetland bed constructed on a slope, and a permeable pond used as a receiver. The test treatment plant was located at a mountain eco-tourist farm on the periphery of the spa municipality of Krynica-Zdrój, Poland. The plant's operational reliability in reducing the concentration of organic matter, measured as biochemical oxygen demand (BOD) and chemical oxygen demand (COD), was 100% when modelled by both the Weibull and the lognormal distributions. The respective reliability values for total nitrogen removal were 76.8% and 77.0%, total suspended solids - 99.5% and 92.6%, and PO-P - 98.2% and 95.2%, with the differences being negligible. The installation was characterized by a very high level of technological reliability when compared with other solutions of this type. The Weibull method employed for statistical evaluation of technological reliability can also be used for comparison purposes. From the ecological perspective, the facility presented in the study has proven to be an effective tool for protecting local aquifer areas.
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http://dx.doi.org/10.2166/wst.2017.139 | DOI Listing |
Sci Justice
September 2025
Centre international de criminologie comparée, Canada; École de criminologie, Université de Montréal, Canada.
Technology's rapid evolution has made digital traces a common part of our lives, holding significant value for investigations and legal cases across various national jurisdictions. However, law enforcement and judicial systems often struggle to adapt to these changes, resulting in possible misinterpretations of digital evidence in criminal trials. Drawing on insights from a qualitative analysis of a terrorism-related court case, this research aims to gain a deeper understanding of the fundamental challenges of decision-making in digital forensics and how they can impact a criminal case.
View Article and Find Full Text PDFInt J Sport Nutr Exerc Metab
September 2025
Mary MacKillop Institute for Health Research, Australian Catholic University, Melbourne, VIC, Australia.
Technological innovations can provide cyclists and their support team additional data. These data have potential to improve understanding of performance determinants and could be used to identify and tailor nutritional strategies to improve cycling performance. This potential, however, is dependent on the quality, interpretation, and practical use of the data generated.
View Article and Find Full Text PDFForensic Sci Int
September 2025
Department of Chemistry, Faculty of Philosophy, Sciences and Letters of Ribeirão Preto, Ribeirão Preto, São Paulo 14040-091, Brazil; Instituto Nacional de Ciência e Tecnologia - Ciências Forenses (INCT Forense), Department of Chemistry, Faculty of Philosophy, Sciences and Letters of Ribeirão P
New psychoactive substances (NPS) present significant challenges for law enforcement and public health due to their rapid emergence and structural diversity, often outpacing the development of traditional analytical methods. This review explores using computational chemistry, particularly density functional theory (DFT), to obtain infrared spectra. This combination to characterize NPS began in the 2010s and has gained momentum across all continents in recent years.
View Article and Find Full Text PDFJ AOAC Int
September 2025
Analytical Development Division, Senores Pharmaceuticals, Ahmedabad, India.
Background: Molnupiravir, an FDA-approved antiviral for the treatment of COVID-19, requires reliable analytical methods to ensure its quality and safety due to its therapeutic importance.
Objectives: This study presents the development of a stability-indicating RP-HPLC method for estimating molnupiravir-related impurities in capsule formulations. An unknown impurity is structurally elucidated using LC-TQ/MS and 1H and 1³C NMR spectroscopy.
Cell Syst
September 2025
Broad Institute of MIT and Harvard, Cambridge, MA 02142, USA; Data Sciences Platform, Broad Institute of MIT and Harvard, Cambridge, MA 02142, USA. Electronic address:
Spatial transcriptomics allows for the measurement of gene expression within the native tissue context. However, despite technological advancements, computational methods to link cell states with their microenvironment and compare these relationships across samples and conditions remain limited. To address this, we introduce Tissue Motif-Based Spatial Inference across Conditions (TissueMosaic), a self-supervised convolutional neural network designed to discover and represent tissue architectural motifs from multi-sample spatial transcriptomic datasets.
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