PiML Toolbox for Interpretable Machine Learning Model Development and Diagnostics

PiML (read $\pi$-ML, /`pai`em`el/) is an integrated and open-access Python toolbox for interpretable machine learning model development and model diagnostics. It is designed with machine learning workflows in both low-code and high-code modes, including data pipeline, model training and tuning, model interpretation and explanation, and model diagnostics and comparison. The toolbox supports a growing list of interpretable models (e.g. GAM, GAMI-Net, XGB1/XGB2) with inherent local and/or global interpretability. It also supports model-agnostic explainability tools (e.g. PFI, PDP, LIME, SHAP) and a powerful suite of model-agnostic diagnostics (e.g. weakness, reliability, robustness, resilience, fairness). Integration of PiML models and tests to existing MLOps platforms for quality assurance are enabled by flexible high-code APIs. Furthermore, PiML toolbox comes with a comprehensive user guide and hands-on examples, including the applications for model development and validation in banking. The project is available at https://github.com/SelfExplainML/PiML-Toolbox

The influence of Unmanned Agricultural Aircraft System design on spray drift

Es wurden Feldversuche durchgeführt, um den Einfluss der Bauart von unbemannten Luftfahrzeugen (Unmanned Agricultural Aircraft Systems, UAAS) auf das Bodense­diment der Abdrift im Ackerbau festzustellen. Zudem wurde die Verteilung der Spritzflüssigkeit auf der Behand­lungsfläche ermittelt. Zusätzlich wurde als mögliche Alternative zur Messung des Bodensediments auch das luftgetragene Abdriftpotenzial am Rand der Behandlungsfläche bestimmt.Vier verschiedene UAAS dreier unterschiedlicher Bauarten, ein 1-Rotor-, ein 6-Rotor- und zwei 8-Rotor-UAAS wurden untersucht. Alle UAAS hatten unterschiedliche Spritzgestänge, wurden aber jeweils mit gleichen Düsen bestückt: Lechler TR 80–0067 und Lechler IDK 120–015, mit denen jeweils 40 l ha–1 bzw. 75 l ha–1 appliziert wurden.Weder für die UAAS-Bauart noch für die Düse konnte ein Einfluss auf die Verteilung der Spritzflüssigkeit auf der Behandlungsfläche festgestellt werden; der Variationskoeffizient der Querverteilung lag generell zwischen 40% und 50%.Die Untersuchungsergebnisse zeigen, dass der Einfluss der UAAS-Bauart gegenüber dem Einfluss der Düse vernachlässigbar ist. Wie bei anderen Pflanzenschutzgeräten verursachte die Hohlkegeldüse TR 80–0067 wesentlich mehr Abdrift als die Luftinjektor-Flachstrahldüse IDK 120–015. Bei beiden Düsentypen lag das Bodensediment wesentlich über den in Deutschland für die Risikobewertung im Ackerbau verwendeten Abdrifteckwerten.Zwischen dem Bodensediment und dem am Rand der Behandlungsfläche ermittelten luftgetragenen Abdriftpotenzial wurde eine enge Korrelation gefunden. Somit scheint das Abdriftpotenzial eine brauchbare Alternative, zumindest für den Vergleich unterschiedlicher Appli­kationstechniken, darzustellen. Für gesicherte Aussagen hierzu sind jedoch weitere Untersuchungen notwendig.Field experiments were conducted to determine the influence of the Unmanned Agricultural Aircraft Systems (UAAS) design on spray drift sediment during a common arable field application in consideration of the spray deposit distribution. In addition, airborne drift collectors were used to determine the initial drift potential as a possible alternative for characterising the spray drift.Four models of UAAS representing three different designs, one single rotor, one 6-rotor and two 8-rotor designs, were involved in the study. All UAASs where equipped with individual spraying systems but the same nozzles were used: Lechler TR 80–0067 and Lechler IDK 120–015, providing nominal application rates of 40 l ha–1 and 75 l ha–1, respectively.There was no influence of the UAAS design or the nozzle type on the spray distribution quality on the treated area. In general, the coefficient of spray deposit variation was 40% to 50%.The results of the study show that the effect of the UAAS design on spray drift was relatively low compared to the influence of the type of nozzles used. As for other application techniques, the conventional hollow cone nozzle TR 80–0067 produced much more spray drift compared to the air induction flat fan nozzle IDK 120–015. With both types of nozzles, the ground sediment of spray drift was much higher than the standard drift values used by German authorities for drift risk assessments for boom sprayers in arable crops.A good correlation was found between drift sediment and airborne drift potential. As the latter seems to be a suitable alternative, at least for comparing different spraying systems, further studies should be conducted also for other application techniques

Adult Repellency and Larvicidal Activity of Five Plant Essential Oils Against Mosquitoes

The larvicidal activity and repellency of 5 plant essential oils—thyme oil, catnip oil, amyris oil, eucalyptus oil, and cinnamon oil—were tested against 3 mosquito species: Aedes albopictus, Ae. aegypti, and Culex pipiens pallens. Larvicidal activity of these essentials oils was evaluated in the laboratory against 4th instars of each of the 3 mosquito species, and amyris oil demonstrated the greatest inhibitory effect with LC50 values in 24 h of 58 µg/ml (LC90  =  72 µg/ml) for Ae. aegypti, 78 µg/ml (LC90  =  130 µg/ml) for Ae. albopictus, and 77 µg/ml (LC90  =  123 µg/ml) for Cx. p. pallens. The topical repellency of these selected essential oils and deet against laboratory-reared female blood-starved Ae. albopictus was examined. Catnip oil seemed to be the most effective and provided 6-h protection at both concentrations tested (23 and 468 µg/cm2). Thyme oil had the highest effectiveness in repelling this species, but the repellency duration was only 2 h. The applications using these natural product essential oils in mosquito control are discussed

Gut microbiota and its metabolites in non-small cell lung cancer and brain metastasis: from alteration to potential microbial markers and drug targets

BackgroundThe elevated mortality rate associated with non–small-cell lung cancer (NSCLC) is a well-established global concern. Considerable attention has been directed toward exploring the association between gut microbiota and various malignant tumors. We herein investigated the associations between the intestinal microbiome and its metabolites, particularly short-chain fatty acids (SCFAs), in patients with NSCLC at different stages, including early and brain metastasis (BM) stages. The findings aim to offer a fresh perspective on the diagnosis and management of NSCLC.MethodsFecal samples were collected from 115 participants, comprising healthy controls (n = 35) and patients with treatment-naive NSCLC at the early stage (ELC, n = 40) and the BM stage (n = 40). Characterization of the intestinal microbiome and fecal SCFA levels was performed using 16S rRNA gene sequencing and gas chromatography.ResultsThe microbial diversity in patients with NSCLC was found to be less abundant and uniform, particularly in the BM stage. Significant alterations in the community structure of the gut microbiota were observed in patients with NSCLC, with an increase in pathogens in Fusobacteria and Proteobacteria and a decrease in SCFA-producing bacteria in Firmicutes and Actinobacteria, particularly in the BM stage. Meanwhile, microbial communities displayed intricate associations in patients with NSCLC. A biomarker panel (Faecalibacterium, Bifidobacterium, Butyricicoccus, Klebsiella, Streptococcus, and Blautia) successfully distinguished patients in the ELC and BM stages from healthy controls (area under the curve: 0.884). The overall concentration of fecal SCFAs was significantly lower in patients with BM compared to patients with ELC and healthy controls. Subgroup analysis of acetate and butyrate yielded similar results. Moreover, multiple disrupted pathways in the NSCLC group were identified using the Kyoto Encyclopedia of Genes and Genomes annotation, including lipid metabolism and genetic information processing, specifically in the BM stage.ConclusionCompared with healthy controls, distinct host-microbe interactions were evident in different phases of patients with NSCLC. Furthermore, specific forms of the gut microbiome and SCFAs may serve as valuable biomarkers and therapeutic targets in the diagnosis and treatment of NSCLC

Lipase production by solid-state fermentation of olive pomace in tray-type and pressurized bioreactors

Background: Bioreactor type, sterilization and specific operational conditions are key factors for the scale-up of solid-state fermentation (SSF). This work deals with the lipase production by SSF of olive pomace (OP) at a traditional tray-type and pressurized bioreactors. Important aspects for SSF at bioreactors were studied, such as the need of sterilization and moisture content (MC) control. RESULTS At larger scale, there was no significant difference in lipase production between sterilized and unsterilized substrates, but MC control had significant impact. The production of lipase in a pressurized bioreactor, under air absolute pressure of 200 kPa and 400 kPa, was two-fold higher than in tray-type bioreactor using the same amount of substrate (500 g) and the same bed height. The protein content of substrate increased from 10 to 18% (w/w) after SSF and the fermented solid presented an antioxidant activity of 10 mmol Trolox kg-1. CONCLUSIONS SSF in pressurized bioreactor allowed to efficiently produce lipase with higher substrate bed height in contrast to that in tray-type bioreactor. The improvement of nutritional value of substrate by SSF indicates its potential applicability in animal feed.Felisbela Oliveira acknowledges the financial support from the Portuguese Foundation for Science and Technology (FCT) through grant SFRH/BD/87953/2012. José Manuel Salgado was supported by grant CEB/N2020 – INV/01/2016 from Project “BIOTECNORTE - Underpinning Biotechnology to foster the north of Portugal bioeconomy” (NORTE-01-0145-FEDER-000004). This study was supported by the Portuguese Foundation for Science and Technology (FCT) under the scope of the strategic funding of UID/BIO/04469/2013 unit and COMPETE 2020 (POCI-01-0145-FEDER-006684) and BioTec-Norte operation (NORTE-01-0145-FEDER-000004) funded by the European Regional Development Fund under the scope of Norte2020 ProgramaOperacionalRegionaldoNorte. Noelia Pérez-Rodríguez acknowledges the financial support of FPU from Spanish Ministry of Education, Culture and Sports. The authors thank the Spanish Ministry of Science and Innovation for the financial support of this work (projectCTQ2011-28967), which has partial financial support from the FEDER funds of the European Union.info:eu-repo/semantics/publishedVersio

GWAS Identifies Novel Susceptibility Loci on 6p21.32 and 21q21.3 for Hepatocellular Carcinoma in Chronic Hepatitis B Virus Carriers

Genome-wide association studies (GWAS) have recently identified KIF1B as susceptibility locus for hepatitis B virus (HBV)–related hepatocellular carcinoma (HCC). To further identify novel susceptibility loci associated with HBV–related HCC and replicate the previously reported association, we performed a large three-stage GWAS in the Han Chinese population. 523,663 autosomal SNPs in 1,538 HBV–positive HCC patients and 1,465 chronic HBV carriers were genotyped for the discovery stage. Top candidate SNPs were genotyped in the initial validation samples of 2,112 HBV–positive HCC cases and 2,208 HBV carriers and then in the second validation samples of 1,021 cases and 1,491 HBV carriers. We discovered two novel associations at rs9272105 (HLA-DQA1/DRB1) on 6p21.32 (OR = 1.30, P = 1.13×$10^{−19}$) and rs455804 (GRIK1) on 21q21.3 (OR = 0.84, P = 1.86×$10^{−8}$), which were further replicated in the fourth independent sample of 1,298 cases and 1,026 controls (rs9272105: OR = 1.25, P = 1.71×$10^{−4}$; rs455804: OR = 0.84, P = 6.92×$10^{−3}$). We also revealed the associations of HLA-DRB1*0405 and 0901*0602, which could partially account for the association at rs9272105. The association at rs455804 implicates GRIK1 as a novel susceptibility gene for HBV–related HCC, suggesting the involvement of glutamate signaling in the development of HBV–related HCC

Iris Recognition Method Based on Parallel Iris Localization Algorithm and Deep Learning Iris Verification

Biometric recognition technology has been widely used in various fields of society. Iris recognition technology, as a stable and convenient biometric recognition technology, has been widely used in security applications. However, the iris images collected in the actual non-cooperative environment have various noises. Although mainstream iris recognition methods based on deep learning have achieved good recognition accuracy, the intention is to increase the complexity of the model. On the other hand, what the actual optical system collects is the original iris image that is not normalized. The mainstream iris recognition scheme based on deep learning does not consider the iris localization stage. In order to solve the above problems, this paper proposes an effective iris recognition scheme consisting of the iris localization and iris verification stages. For the iris localization stage, we used the parallel Hough circle to extract the inner circle of the iris and the Daugman algorithm to extract the outer circle of the iris, and for the iris verification stage, we developed a new lightweight convolutional neural network. The architecture consists of a deep residual network module and a residual pooling layer which is introduced to effectively improve the accuracy of iris verification. Iris localization experiments were conducted on 400 iris images collected under a non-cooperative environment. Compared with its processing time on a graphics processing unit with a central processing unit architecture, the experimental results revealed that the speed was increased by 26, 32, 36, and 21 times at 4 different iris datasets, respectively, and the effective iris localization accuracy is achieved. Furthermore, we chose four representative iris datasets collected under a non-cooperative environment for the iris verification experiments. The experimental results demonstrated that the network structure could achieve high-precision iris verification with fewer parameters, and the equal error rates are 1.08%, 1.01%, 1.71%, and 1.11% on 4 test databases, respectively