Effect of injury on negative phototaxis. by Ella R. Dockendorf (21533334)

Effects of injury on operant conditioning and memory. by Ella R. Dockendorf (21533334)

Effects of injury on exploratory behavior. by Ella R. Dockendorf (21533334)

Retention and extinction of operant learning. by Ella R. Dockendorf (21533334)

Global Land Use Change Impacts on Soil Nitrogen Availability and Environmental Losses by Jing Wang (6206297)

“…However, how global land use changes impact soil N supply and potential N loss remains elusive. By compiling a global data set of 1,782 paired observations from 185 publications, we show that land use conversion from natural to managed ecosystems significantly reduced NNM by 7.5% (−11.5, −2.8%) and increased NN by 150% (86, 194%), indicating decreasing N availability while increasing potential N loss through denitrification and nitrate leaching. …”

Minimal data set. by Fu-Lin Yu (21446056)

S1 Data - by Beat Knechtle (5504402)

“…For both women and men, the smallest sex difference was least significant in age group 18–24 years for all split disciplines and increased in a U-shaped manner until age group 70–74 years. …”

S2 Data - by Beat Knechtle (5504402)

“…For both women and men, the smallest sex difference was least significant in age group 18–24 years for all split disciplines and increased in a U-shaped manner until age group 70–74 years. …”

Average split and overall race times (HH:MM:SS). by Beat Knechtle (5504402)

“…For both women and men, the smallest sex difference was least significant in age group 18–24 years for all split disciplines and increased in a U-shaped manner until age group 70–74 years. …”

Men-to-women ratio across age groups. by Beat Knechtle (5504402)

“…For both women and men, the smallest sex difference was least significant in age group 18–24 years for all split disciplines and increased in a U-shaped manner until age group 70–74 years. …”

Addressing Imbalanced Classification Problems in Drug Discovery and Development Using Random Forest, Support Vector Machine, AutoGluon-Tabular, and H2O AutoML by Ayush Garg (21090944)

“…The important findings of our studies are as follows: (i) there is no effect of threshold optimization on ranking metrics such as AUC and AUPR, but AUC and AUPR get affected by class-weighting and SMOTTomek; (ii) for ML methods RF and SVM, significant percentage improvement up to 375, 33.33, and 450 over all the data sets can be achieved, respectively, for F1 score, MCC, and balanced accuracy, which are suitable for performance evaluation of imbalanced data sets; (iii) for AutoML libraries AutoGluon-Tabular and H2O AutoML, significant percentage improvement up to 383.33, 37.25, and 533.33 over all the data sets can be achieved, respectively, for F1 score, MCC, and balanced accuracy; (iv) the general pattern of percentage improvement in balanced accuracy is that the percentage improvement increases when the class ratio is systematically decreased from 0.5 to 0.1; in the case of F1 score and MCC, maximum improvement is achieved at the class ratio of 0.3; (v) for both ML and AutoML with balancing, it is observed that any individual class-balancing technique does not outperform all other methods on a significantly higher number of data sets based on F1 score; (vi) the three external balancing techniques combined outperformed the internal balancing methods of the ML and AutoML; (vii) AutoML tools perform as good as the ML models and in some cases perform even better for handling imbalanced classification when applied with imbalance handling techniques. …”

Fig 3 - by Asnake Adane (19935018)

Variable settings and assignment descriptions. by Yuling Jin (11872953)

Data set. by Ana Belén López Pérez (22693281)

“…<div><p>This study documents the introduction process of eight unrelated captive male Asian elephants in a free-contact management setting in Laos, utilizing a two-phase introduction process comprising limited tactile contact followed by full physical introduction. …”

Parameter Settings. by Yutong Liu (4027994)

IRE1 silencing downregulates cell cycle genes and engages TP53 and specific CDK inhibitors. by Iratxe Zuazo-Gaztelu (21071939)

Training impact on electrical properties of P3 lumbar MNs. Rin: input resistance. Rheobase: lowest intensity of current injected in MNs to elicit an action potential (AP). AP thres... by Camille Quilgars (21156495)

Species and numbers of individuals caught on reef-cages and in reference traps. by Maryann S. Watson (16879881)

Fig 6 - by Maryann S. Watson (16879881)

Fig 4 - by Maryann S. Watson (16879881)