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We measured the cross sections for the formation of the ground state nucleus 100gRh through natPd(p,x)100m,gRh reactions. The experiment was carried out using the stacked-foil activation technique in the energy range from threshold to 42.61 MeV. The cross section was determined on the basis of the measured activity of the corresponding residual nucleus using a high energy resolution HPGe γ-ray detector. The energy dependent flux of the proton beam was determined using the natCu(p,x)62Zn and natCu(p,x)65Zn monitoring reactions. In order to enhance the accuracy of the experimental results, the activity contributions from the decay of the 100mAg, 100gAg and 100Pd to 100gRh, which were also produced in the same palladium foil were corrected. The present experimental results are compared with the previously published data and with the theoretical predictions from the TENDL-2017 library.

High‐throughput sequencing has the potential to describe biological communities with high efficiency yet comprehensive assessment of diversity with species‐level resolution remains one of the most challenging aspects of metabarcoding studies. We investigated the utility of curated ribosomal and mitochondrial nematode reference sequence databases for determining phylum‐specific species‐level clustering thresholds. We compiled 438 ribosomal and 290 mitochondrial sequences which identified 99% and 94% as the species delineation clustering threshold, respectively. These thresholds were evaluated in HTS data from mock communities containing 39 nematode species as well as environmental samples from Vietnam. We compared the taxonomic description of the mocks generated by two read‐merging and two clustering algorithms and the cluster‐free Dada2 pipeline. Taxonomic assignment with the RDP classifier was assessed under different training sets. Our results showed that 36/39 mock nematode species were identified across the molecular markers (18S: 32, JB2: 19, JB3: 21) in UClust_ref OTUs at their respective clustering thresholds, outperforming UParse_denovo and the commonly used 97% similarity. Dada2 generated the most realistic number of ASVs (18S: 83, JB2: 75, JB3: 82), collectively identifying 30/39 mock species. The ribosomal marker outperformed the mitochondrial markers in terms of species and genus‐level detections for both OTUs and ASVs. The number of taxonomic assignments of OTUs/ASVs was highest when the smallest reference database containing only nematode sequences was used and when sequences were truncated to the respective amplicon length. Overall, OTUs generated more species‐level detections, which were, however, associated with higher error rates compared to ASVs. Genus‐level assignments using ASVs exhibited higher accuracy and lower error rates compared to species‐level assignments, suggesting that this is the most reliable pipeline for rapid assessment of alpha diversity from environmental samples.

We measured the excitation functions for the production of the radionuclides $$^{{95}}\hbox {Zr}$$ , $$^{95\mathrm {m}}\hbox {Nb}$$ and $$^{95\mathrm {g}}\hbox {Nb}$$ from the $$^{\mathrm {nat}}\hbox {Zr}(\hbox {p},\hbox {x})$$ reactions in the proton energy range of 10.6–43.6 MeV. The experiment was performed by irradiation of zirconium and copper foils simultaneously using 45 MeV proton beam from the MC-50 Cyclotron at the Korea Institute of Radiological and Medical Sciences, Korea, and the induced activity was measured with an HPGe $$\upgamma $$ -ray detector. Proton energies along the foil stack were calculated using the computer code SRIM-2013. The proton beam flux entered each foil was determined via the $$^{\mathrm {nat}}\hbox {Cu}(\hbox {p},\hbox {x})^{{62}}\hbox {Zn}$$ and $$^{\mathrm {nat}}\hbox {Cu}(\hbox {p},\hbox {x})^{{65}}\hbox {Zn}$$ monitoring reactions. The cumulative cross sections of the $$^{\mathrm {nat}}\hbox {Zr}(\hbox {p},\hbox {x})^{{95}}\hbox {Zr}$$ reaction were measured because it was unable to separate the activity from the decay of $$^{{95}}\hbox {Y}$$ to $$^{{95}}\hbox {Zr}$$ . However, independent cross sections of the $$^{\mathrm {nat}}\hbox {Zr}(\hbox {p},\hbox {x})^{95\mathrm {m}}\hbox {Nb}$$ and $$^{\mathrm {nat}}\hbox {Zr}(\hbox {p},\hbox {x})^{95\mathrm {g}}\hbox {Nb}$$ reactions were determined, since the independent activities of $$^{95\mathrm {m}}\hbox {Nb}$$ and $$^{95\mathrm {g}}\hbox {Nb}$$ can also be measured. In addition, the thick target yields of the $$^{{95}}\hbox {Zr}$$ , $$^{95\mathrm {m}}\hbox {Nb}$$ and $$^{95\mathrm {g}}\hbox {Nb}$$ isotopes were also determined. The current results are compared with the previously measured data as well as with the theoretical values from the TALYS-1.9 code and the TENDL-2019 data library.

Nematodes are suitable indicators for environmental perturbations because their distribution is closely linked to sediment characteristics. To evaluate whether DNA-based approaches can complement or even outperform morphology-based monitoring, careful evaluation of both approaches is needed using field samples that clearly differ in environmental parameters. We compared metabarcoding, targeting the 18S rRNA and COI genes, with morphological identification of the nematode communities in three different land use areas (aquaculture, industry and nature reserve) in Vietnamese mangroves. The areas differed in heavy metal and nitrate content and granulometry. We additionally generated reference Sanger sequences from these areas in order to improve the genus and species level assignments of the metabarcode data. We compared nematode densities, species and genus composition and diversity estimates, and nematode specific indices in relation to the environmental differences between areas. Our results show that multivariate patterns were similar between the three approaches, while the 18S rRNA metabarcoding dataset best described changes in diversity and community composition in relation to the environmental differences in our sites. The taxonomic composition of the samples was strikingly different depending on the method and less taxa were detected using DNA based methods than the morphology-based method. We show that this is mainly attributed to a lack of entries in the reference databases. The 18S rRNA metabarcoding approach provides a reliable and fast way to screen for environmental changes. Nevertheless, when we also want to understand those changes, the ecological and biological information linked to taxonomy remain essential. We therefore advocate that the addition of new reference sequences from vouchered specimens to reference databases should be an essential part of every metabarcoding study.