23 research outputs found
Siamese Basis Function Networks for Data-Efficient Defect Classification in Technical Domains
Training deep learning models in technical domains is often accompanied by the challenge that although the task is clear, insufficient data for training is available. In this work, we propose a novel approach based on the combination of Siamese networks and radial basis function networks to perform data-efficient classification without pretraining by measuring the distance between images in semantic space in a data-efficient manner. We develop the models using three technical datasets, the NEU dataset, the BSD dataset, and the TEX dataset. In addition to the technical domain, we show the general applicability to classical datasets (cifar10 and MNIST) as well. The approach is tested against state-of-the-art models (Resnet50 and Resnet101) by stepwise reduction of the number of samples available for training. The authors show that the proposed approach outperforms the state-of-the-art models in the low data regime
SHAPE: A Framework for Evaluating the Ethicality of Influence
Agents often exert influence when interacting with humans and non-human
agents. However, the ethical status of such influence is often unclear. In this
paper, we present the SHAPE framework, which lists reasons why influence may be
unethical. We draw on literature from descriptive and moral philosophy and
connect it to machine learning to help guide ethical considerations when
developing algorithms with potential influence. Lastly, we explore mechanisms
for governing algorithmic systems that influence people, inspired by mechanisms
used in journalism, human subject research, and advertising.Comment: An earlier version of this paper was accepted at EUMAS 202
Effects of Agricultural Productivity Shocks on Female Labor Supply: Evidence from the Boll Weevil Plague in the US South
In the beginning of the 1890s, counties located in the Cotton Belt of the American South were hit by an agricultural plague, the boll weevil, that adversely affected cotton production and hence the demand for labor. We use variation in the incidence of the boll weevil multiplied with counties’ initial cotton share to construct instrumental variables estimates of the labor supply curve. Controlling for county and state-by-time fixed effects, we find a significant positive response of labor supply to changes in labor income. The effect is particularly large for females, consistent with evidence that females had a comparative advantage in picking cotton
Effects of Agricultural Productivity Shocks on Female Labor Supply: Evidence from the Boll Weevil Plague in the US South
In the beginning of the 1890s, counties located in the Cotton Belt of the American South were hit by an agricultural plague, the boll weevil, that adversely affected cotton production and hence the demand for labor. We use variation in the incidence of the boll weevil multiplied with counties’ initial cotton share to construct instrumental variables estimates of the labor supply curve. Controlling for county and state-by-time fixed effects, we find a significant positive response of labor supply to changes in labor income. The effect is particularly large for females, consistent with evidence that females had a comparative advantage in picking cotton
Effects of Agricultural Productivity Shocks on Female Labor Supply: Evidence from the Boll Weevil Plague in the US South
In the beginning of the 1890s, counties located in the Cotton Belt of the American South were hit by an agricultural plague, the boll weevil, that adversely affected cotton production and hence the demand for labor. We use variation in the incidence of the boll weevil multiplied with counties’ initial cotton share to construct instrumental variables estimates of the labor supply curve. Controlling for county and state-by-time fixed effects, we find a significant positive response of labor supply to changes in labor income. The effect is particularly large for females, consistent with evidence that females had a comparative advantage in picking cotton
Development of a PROTAC-Based Targeting Strategy Provides a Mechanistically Unique Mode of Anti-Cytomegalovirus Activity
Human cytomegalovirus (HCMV) is a major pathogenic herpesvirus that is prevalent worldwide and it is associated with a variety of clinical symptoms. Current antiviral therapy options do not fully satisfy the medical needs; thus, improved drug classes and drug-targeting strategies are required. In particular, host-directed antivirals, including pharmaceutical kinase inhibitors, might help improve the drug qualities. Here, we focused on utilizing PROteolysis TArgeting Chimeras (PROTACs), i.e., hetero-bifunctional molecules containing two elements, namely a target-binding molecule and a proteolysis-inducing element. Specifically, a PROTAC that was based on a cyclin-dependent kinase (CDK) inhibitor, i.e., CDK9-directed PROTAC THAL-SNS032, was analyzed and proved to possess strong anti-HCMV AD169-GFP activity, with values of EC50 of 0.030 µM and CC50 of 0.175 µM (SI of 5.8). Comparing the effect of THAL-SNS032 with its non-PROTAC counterpart SNS032, data indicated a 3.7-fold stronger anti-HCMV efficacy. This antiviral activity, as illustrated for further clinically relevant strains of human and murine CMVs, coincided with the mid-nanomolar concentration range necessary for a drug-induced degradation of the primary (CDK9) and secondary targets (CDK1, CDK2, CDK7). In addition, further antiviral activities were demonstrated, such as the inhibition of SARS-CoV-2 replication, whereas other investigated human viruses (i.e., varicella zoster virus, adenovirus type 2, and Zika virus) were found insensitive. Combined, the antiviral quality of this approach is seen in its (i) mechanistic uniqueness; (ii) future options of combinatorial drug treatment; (iii) potential broad-spectrum activity; and (iv) applicability in clinically relevant antiviral models. These novel data are discussed in light of the current achievements of anti-HCMV drug development
Metal-Free Intermolecular C–H Borylation of N-Heterocycles at B–B Multiple Bonds
Carbene-stabilized diborynes of the form LBBL (L = NHC or CAAC) induce rapid, high yielding, intermolecular ortho-C–H borylation at N-heterocycles at room temperature. A simple pyridyldiborene is formed when an NHC-stabilized diboryne is combined with pyridine, while a CAAC-stabilized diboryne leads to activation of two pyridine molecules to give a tricyclic alkylideneborane, which can be forced to undergo a further H-shift resulting in a zwitterionic, doubly benzo-fused 1,3,2,5-diazadiborinine by heating. Use of the extended N-heteroaromatic quinoline leads to a borylmethyleneborane under mild conditions via an unprecedented boron-carbon exchange process
Metallfreie intermolekulare C-H-Borylierung von N-Heterocyclen an B-B-Mehrfachbindungen
Carbenstabilisierte Diborine der Form LBBL (L=N-heterocyclisches Carben (NHC) oder cyclisches Alkyl(amino)carben (CAAC)) induzieren bei Raumtemperatur eine schnelle, ertragreiche, intermolekulare ortho-C-H-Borylierung an N-Heterocyclen. Ein einfaches Pyridyldiboren wird gebildet, wenn ein NHC-stabilisiertes Diborin mit Pyridin kombiniert wird, während ein CAAC-stabilisiertes Diborin zur Aktivierung von zwei Pyridinmolekülen führt, um ein tricyclisches Alkylidenboran zu bilden, das durch Erhitzen zu einem zwitterionischen, zweifach benzokondensierten 1,3,2,5-Diazadiborinin mittels einer weiteren H-Verschiebung umgelagert werden kann. Die Verwendung des verlängerten N-heteroaromatischen Chinolins führt unter milden Bedingungen über einen bisher unbekannten Bor-Kohlenstoff-Austauschprozess zu einem Borylmethylenboran