Test Maintenance for Machine Learning Systems: A Case Study in the Automotive Industry

Machine Learning (ML) systems have seen widespread use for automated decision making. Testing is essential to ensure the quality of these systems, especially safety-critical autonomous systems in the automotive domain. ML systems introduce new challenges with the potential to affect test maintenance, the process of updating test cases to match the evolving system. We conducted an exploratory case study in the automotive domain to identify factors that affect test maintenance for ML systems, as well as to make recommendations to improve the maintenance process. Based on interview and artifact analysis, we identified 14 factors affecting maintenance, including five especially relevant for ML systems—with the most important relating to non-determinism and large input spaces. We also proposed ten recommendations for improving test maintenance, including four targeting ML systems—in particular, emphasizing the use of test oracles tolerant to acceptable non-determinism. The study’s findings expand our knowledge of test maintenance for an emerging class of systems, benefiting the practitioners testing these systems

Catalytic and structural diversity of the fluazifop-inducible glutathione transferases from Phaseolus vulgaris

Plant glutathione transferases (GSTs) comprise a large family of inducible enzymes that play important roles in stress tolerance and herbicide detoxification. Treatment of Phaseolus vulgaris leaves with the aryloxyphenoxypropionic herbicide fluazifop-p-butyl resulted in induction of GST activities. Three inducible GST isoenzymes were identified and separated by affinity chromatography. Their full-length cDNAs with complete open reading frame were isolated using RACE-RT and information from N-terminal amino acid sequences. Analysis of the cDNA clones showed that the deduced amino acid sequences share high homology with GSTs that belong to phi and tau classes. The three isoenzymes were expressed in E. coli and their substrate specificity was determined towards 20 different substrates. The results showed that the fluazifop-inducible glutathione transferases from P. vulgaris (PvGSTs) catalyze a broad range of reactions and exhibit quite varied substrate specificity. Molecular modeling and structural analysis was used to identify key structural characteristics and to provide insights into the substrate specificity and the catalytic mechanism of these enzymes. These results provide new insights into catalytic and structural diversity of GSTs and the detoxifying mechanism used by P. vulgaris

Isolation of GST isoenzymes from Phaseolus vulgaris L. and characterization of detoxifying mechanism under biotic and abiotic stress

Three Glutathione transferase (GSTs) isoenzymes have been isolated from P. vulgaris leaves after in vivo treatment with 1/250 fluazifop-p-butyl herbicide. The inducible GST isoenzymes were identified and separated by affinity chromatography. They found to belong to phi and tau classes. Moreover, the fluazifop-inducible glutathione transferases from P. vulgaris (PvGSTs, termed PvGSTU2-2, PvGSTF1-1 and PvGSTU3-3) were found to catalyze a broad range of reactions and exhibit quite varied substrate specificity. Another GST isoenzyme was isolated from P. vulgaris (PvGST, termed PvGSTU3-3), after its induction with biotic stress treatment (Uromyces appendiculatus infection). PvGSTU3-3 shares high homology the tau class plant and catalyzes several different reactions and exhibits wide substrate specificity. Of particular importance are the high antioxidant catalytic function and hydroperoxidase, thioltransferase, and dehydroascorbate reductase action of Pv-GSTU3-3. Transgenic tobacco plants over-expressing PvGSTU2-2 isoenzyme have been developed via Agrobacteriun tumefaciens in order to study their in planta potential to confer biotic and abiotic resistance as a means of plant breeding. Our results provide new insights into catalytic and structural diversity of GSTs and the detoxifying mechanism used by P. vulgaris. Moreover, highlight the functional and catalytic diversity of plant GSTs and demonstrate their pivotal role for addressing biotic stresses in P. vulgaris

Could energy equilibrium and greenhouse gas emissions in agroecosystems play a key role in crop replacement? A case study in orange and kiwi orchards

The development of agriculture is linked to energy resources. Consequently, energy analysis in agroecosystems could be a useful tool for monitoring some measures in the agricultural sector to mitigate greenhouse gas emissions. The objectives of this study were to (a) evaluate differences of energy indices in orange and kiwi orchards, and (b) point out whether inputs, outputs, efficiency, productivity, and carbon footprint can play a key role in crop replacement. Proportional stratified random sampling was used to select 26 orchards (10 oranges, 16 kiwis) from the Prefecture of Arta, western Greece, during 2015 and 2016. Univariate statistical methods were combined with multivariate ones. Nitrogen, Mg, Zn, herbicides, insecticides, fungicides, renewable energy inputs, fruit production, total outputs, and energy efficiency and productivity were statistically significantly high in the orange orchards. Phosphorus, Ca, irrigation, machinery, total inputs, intensity, non-renewable energy consumption, and carbon footprint were statistically significantly high in the kiwi orchards. The most important energy inputs for both fruit crops were fertilizers, fuels, irrigation, machinery, and herbicides. The orange orchards seem to be more friendly to the environment than the kiwi orchards by having low total energy inputs 32,210.3 MJ ha−1, intensity 1.4, consumption of non-renewable energy 0.7 MJ kg−1 and CO2 equivalent/fruit production 0.08 kg kg−1, and high energy outputs 105,120.0 MJ ha−1 and fruit production 53,648.0 kg ha−1. The findings of the present study show a relation between climate change and the production of farming systems, which can be a tool for decision makers. The correlation of the above-mentioned parameters ensure higher profits and could help in achieving the best possible sustainable management of the agricultural ecosystems

Shared Tools in Software Organizations: An Empirical Investigation

In the present research, tools and toolchains were investigated through the perspective of being shared within software organizations. Particularly, we conducted a literature review which was combined with a case study, that took place in two software organizations, in Gothenburg, Sweden. The different implications of shared tools and toolchains were studied and especially, their benefits, challenges and suggested characteristics. The important role of interoperability was verified, as did the suitability of a generic software assessment method, to be applied on shared tools. The paper suggests that further work can be conducted on the subject, in order to refine the assessment method and investigate shared tools in ecosystems with external actors

Agro-silvopastoral ecosystems: energy budgets and greenhouse gas emissions

Energy flows in perennial agro and natural ecosystems are essential for their productivity and could be related to greenhouse gas emissions and increasing water demands. Energy indices and carbon and water footprint are useful tools in assessing the interaction between production systems and environmental impact inside Natura 2000 sites and enhancing ecosystem services. The main aims of this study were to: a) determine and compare energy indices, carbon and water footprint of olive groves, orange and kiwi orchards and grasslands within and between two years, located in a Natura 2000 site, using an adjusted Life Cycle Assessment (LCA) method and b) illustrate the importance of farming systems to ecosystem services. Stratified sampling was used to select 36 farm types (12 olive groves, 12 oranges and 12 kiwi orchards) and 12 grasslands from the municipality of Amfilochia, western Greece, during 2018 and 2019. Descriptive data analysis, correlation analysis, ANOVA and Hierarchical Cluster Analysis (HCA) were used to summarize and analyze the data. The main energy contributors for the three farm types were fertilizers and fuel consumption. The only input for the grasslands was animal manure. Energy efficiency showed the highest performance in olive groves followed in descending order by kiwi orchards, grasslands and orange orchards. Concerning carbon footprint the values were the highest for orange orchards, followed in descending order by kiwi orchards, olive groves and grasslands. Total water footprint values were the highest for grasslands and the lowest for olive groves. For both years, regarding HCA, each cluster consisted of the same ecosystems. According to the above mentioned indices, olive groves and grasslands are the most environmental friendly ecosystems. They could contribute in the environmental protection of the Amvrakikos Gulf, a Natura 2000 site. Kiwi orchards, although they are intensive along with the orange ones, seems to be more friendly to the environment than them and their cultivation in this Natura 2000 area could be recommended. Energy indices, carbon and water footprint could be used, in order to highlight the related ecosystem (dis)services.Οι ενεργειακές ροές στα πολυετή αγροτικά και φυσικά οικοσυστήματα, αποτελούν κρίσιμο παράγοντα και σχετίζονται με εκπομπές αερίων του θερμοκηπίου, καθώς και αυξανόμενες ανάγκες σε νερό. Οι δείκτες ενεργειακής ανάλυσης και τα αποτυπώματα άνθρακα και νερού, είναι χρήσιμα εργαλεία αξιολόγησης των παραγωγικών οικοσυστημάτων, ενώ ταυτόχρονα συμβάλλουν στην ανάδειξη των υπηρεσιών οικοσυστήματος. Οι στόχοι της μελέτης ήταν να προσδιοριστούν και εν συνεχεία να συγκριθούν οι δείκτες ενέργειας και τα αποτυπώματα άνθρακα και νερού γεωργικών καλλιεργειών και λιβαδιών που βρίσκονται σε περιοχή Natura 2000 (Αμβρακικός Κόλπος) για δύο έτη (2018 και 2019). Με τη χρήση της προσαρμοσμένης μεθόδου Αποτίμησης του Κύκλου Ζωής (LCA), οι δείκτες αναδείχθηκαν ως εργαλεία διατήρησης των ανάλογων υπηρεσιών οικοσυστήματος. Με τη μέθοδο της στρωματοποιημένης τυχαίας δειγματοληψίας, επελέγησαν 36 τύποι αγροοικοσυστημάτων (12 ελαιώνες, 12 πορτοκαλεώνες και 12 οπωρώνες ακτινιδίων) και 12 λιβαδικά οικοσυστήματα από τον Δήμο Αμφιλοχίας, Δυτική Ελλάδα. Για την ανάλυση των δεδομένων χρησιμοποιήθηκαν: δείκτες περιγραφικής στατιστικής, η ανάλυση συσχετίσεων, η ANOVA και η ιεραρχική ανάλυση σε συστάδες (ΙΑΣ). Οι κύριες εισροές ενέργειας για τους τρεις τύπους αγροοικοσυστημάτων ήταν τα λιπάσματα και η κατανάλωση καυσίμων. Η μόνη εισροή για τα λιβάδια ήταν η κοπριά. Επιπλέον, η αποτελεσματικότητα χρήσης ενέργειας ήταν υψηλότερη στην ελιά, ενώ ακολούθησαν κατά φθίνουσα σειρά το ακτινίδιο, το λιβάδι και το πορτοκάλι. Το αποτύπωμα άνθρακα ήταν υψηλότερο στο πορτοκάλι και ακολούθησαν κατά φθίνουσα σειρά το ακτινίδιο, η ελιά και το λιβάδι. Το πράσινο νερό ήταν υψηλότερο για το λιβάδι και χαμηλότερο για την ελιά, ενώ το μπλε νερό ήταν μηδενικό για το λιβάδι και υψηλότερο για το πορτοκάλι και το ακτινίδιο. Στην ΙΑΣ, κάθε συστάδα αποτελούνταν από τα ίδια οικοσυστήματα. Τα οικοσυστήματα ελαιώνων και λιβαδιών αποδείχθηκαν φιλικότερα προς το περιβάλλον και μπορούν να συμβάλλουν στην περιβαλλοντική προστασία του Αμβρακικού Κόλπου. Η καλλιέργεια ακτινιδίου, φαίνεται να είναι πιο φιλική προς το περιβάλλον συγκριτικά με αυτήν την πορτοκαλιάς και συνιστάται η καλλιέργειά της στην περιοχή έρευνας. Συμπεραίνεται πως οι δείκτες ενέργειας και τα αποτυπώματα άνθρακα και νερού, είναι χρήσιμα προκειμένου να αναδειχθούν οι ανάλογες υπηρεσίες οικοσυστήματος και οι επιπτώσεις στα οικοσυστήματ

The Cutting Edge on Advances in ICT Systems in Agriculture

Modern agriculture has to shoulder the burden of a plethora of challenges associated with demographics, climate change, and natural resources depletion [...

Energy Analysis, and Carbon and Water Footprint for Environmentally Friendly Farming Practices in Agroecosystems and Agroforestry

Agriculture accounts for 5% of the entire energy used worldwide. Most of it is not in a renewable form, so it can be linked to greenhouse gas emissions. According to the Paris Agreement, on climate change, one of its major targets is the reduction of greenhouse gas emissions. Therefore, the agricultural production process must drastically change. Currently, the sustainable use of water is critical for any agricultural development. Agricultural production effects water quality and sufficiency, as well as, freshwater wetlands. Energy balance, carbon, and water footprint are crucial for sustainable agricultural production. Agroforestry systems are important in reducing high inputs of non-renewable energy and greenhouse gas emissions, along with better water use, leading to the most minimal influence on climate change. Energy analysis, carbon, and water footprint can be applied to agroforestry systems’ production. An outline could be applied by adopting a modified—for agricultural production—life cycle assessment methodology to assess energy use, greenhouse gas emissions, and water consumption in agroforestry ecosystems

Development of a Universal Second-Tier Newborn Screening LC–MS/MS Method for Amino Acids, Lysophosphatidylcholines, and Organic Acids

First-tier MS-based newborn screening by flow injection analysis can have high presumptive positive rates, often due to isomeric/isobaric compounds or poor biomarker specificity. These presumptive positive samples can be analyzed by second-tier screening assays employing separations such as liquid chromatography–mass spectrometry (LC–MS/MS), which increases test specificity and drastically reduces false positive referrals. The ability to screen for multiple disorders in a single multiplexed test simplifies workflows and maximizes public health laboratories’ resources. In this study, we developed and validated a highly multiplexed second-tier method for dried blood spots using a hydrophilic interaction liquid chromatography (HILIC) column coupled to an MS/MS system. The LC–MS/MS method was capable of simultaneously detecting second-tier biomarkers for maple syrup urine disease, homocystinuria, methylmalonic acidemia, propionic acidemia, glutaric acidemia type 1, glutaric acidemia type 2, guanidinoacetate methyltransferase deficiency, short-chain acyl-CoA dehydrogenase deficiency, adrenoleukodystrophy, and Pompe disease