Specimens of the Nile puffer, Tetraodon lineatus Linnaeus (Tetraodontiformes: Tetraodontidae), were collected from the Nile River, Qena Governorate, Egypt (26°08′N, 32°42′E), and examined for monogenoidean parasites. A single species, initially identified as Heterobothrium lineatum Morsy, Saady, Abdel-Gaffar, Bashtar, Melhorn, Al Quraishy & Adel, 2012 (Monogenoidea: Diclidophoridae), was recovered from the gill lamellae of six out of seven examined hosts (prevalence = 86%). The taxonomic and phylogenetic status of this helminth was reassessed using an integrative approach combining morphological and molecular data. Comparative morphological analysis revealed that H. lineatum represented a junior subjective synonym of H. fluviatile Euzet & Birgi, 1975. Molecular analysis based on the 28S rDNA gene, representing the first inclusion of H. fluviatile as an ingroup taxon, placed this species within a well-supported clade of Heterobothrium species infecting tetraodontid fishes. Heterobothrium indicum Verma, 2022, a parasite of the goldband goatfish, Upeneus moluccensis (Bleeker) (Mulliformes: Mullidae), is herein transferred to Upenicola Unnithan, 1966 as Upenicola indicus (Verma, 2022) n. comb. The study highlighted the need for further investigation into the taxonomic status of Diclidophora indica Tripathi, 1959, and Neodiclidophora simhai Gupta & Krishna, 1980, as probable members of Heterobothrium. Moreover, Heterobothrium lamothei of Morsy et al. (nec Vidal Martinez & Mendoza-Franco) is regarded as a species inquirenda.

Although many studies on sentiment analysis have been carried out for widely spoken languages, this topic is still immature for Turkish. Most of the works in this language focus on supervised models, which necessitate comprehensive annotated corpora. There are a few unsupervised methods, and they utilize sentiment lexicons either built by translating from English lexicons or created based on corpora. This results in improper word polarities as the language and domain characteristics are ignored. In this paper, we develop unsupervised (domain-independent) and semi-supervised (domain-specific) methods for Turkish, which are based on a set of antonym word pairs as seeds. We make a comprehensive analysis of supervised methods under several feature weighting schemes. We then form ensemble of supervised classifiers and also combine the unsupervised and supervised methods. Since Turkish is an agglutinative language, we perform morphological analysis and use different word forms. The methods developed were tested on two datasets having different styles in Turkish and also on datasets in English to show the portability of the approaches across languages. We observed that the combination of the unsupervised and supervised approaches outperforms the other methods, and we obtained a significant improvement over the state-of-the-art results for both Turkish and English.

Product development, especially in aerospace, has become more and more interconnected with its operational environment. In a constant changing world, the operational environment will be subjected to changes during the life cycle of the product. The operational environment will be affected by not only technical and non-technical perturbations, but also economical, managerial and regulatory decisions, thus requiring a more global product development approach. One way to try tackling such complex and intertwined problem advocates studying the envisioned product or system in the context of system of systems (SoS) engineering. SoSs are all around us, probably in any field of engineering, ranging from integrated transport systems, public infrastructure systems to modern homes equipped with sensors and smart appliances; from cities filling with autonomous vehicle to defence systems.

Since also aerospace systems are certainly affected, this work will present a holistic approach to aerospace product development that tries spanning from needs to technology assessment. The proposed approach will be presented and analysed and key enablers and future research directions will be highlighted from an interdisciplinary point of view. Consideration of the surrounding world will require to look beyond classical engineering disciplines.

The identities of two novel perennial nutsedge biotypes collected near Bakersfield, CA, were assessed using isozyme and random-amplified polymorphic deoxyribonucleic acid markers in conjunction with morphological analysis. The two biotypes, designated as CK (Cyperus rotundus cv. ‘Kempeni’) and CR (Cyperus esculentus cv. ‘Robusta’), morphologically resemble purple nutsedge and yellow nutsedge, respectively. Plants from both biotypes exhibited more prolific growth than the typical forms and possessed some traits that are not characteristic of the species they resemble. The morphological study was conducted on a total of 15 purple nutsedge, yellow nutsedge, CK, and CR populations collected in the first year and on 20 additional nutsedge populations were collected in the second year. The genetic analysis was performed on populations from the first year only. In general, there was agreement among the results obtained from the morphometric, isozymatic, and deoxyribonucleic acid studies. Populations of CR clustered with yellow nutsedge populations, indicating that CR is within the normal range of variation of this species and may represent a new introduction. Populations of CK, however, were distinct from both purple nutsedge and yellow nutsedge populations. Considering the low level of genetic variation reported in purple nutsedge and its strict vegetative mode of reproduction, CK might represent a sexually reproducing ecotype of purple nutsedge or a hybrid with yellow nutsedge.

To shed some light on possible directions for research and public policies, but also to help equine industry stakeholders to prepare for upcoming changes, the French National Institute for Agricultural Research (INRA), together with the French Institute for Horse and Horse Riding (IFCE), have conducted a collective scenario-building exercise for the French equine industry to 2030. The study is based on “morphological analysis”, a method which explores past and current trends, and potential shifts in order to consider possible future developments.