Miracle-dz/UniFAR-FTUs huggingface dataset:
Algorithmic Recourse: from Counterfactual Explanations to Interventions

As machine learning is increasingly used to inform consequential decision-making (e.g., pre-trial bail and loan approval), it becomes important to explain how the system arrived at its decision, and also suggest actions to achieve a favorable decision. Counterfactual explanations -"how the world would have (had) to be different for a desirable outcome to occur"- aim to satisfy these criteria. Existing works have primarily focused on designing algorithms to obtain counterfactual explanations for a wide range of settings. However, it has largely been overlooked that ultimately, one of the main objectives is to allow people to act rather than just understand. In layman's terms, counterfactual explanations inform an individual where they need to get to, but not how to get there. In this work, we rely on causal reasoning to caution against the use of counterfactual explanations as a recommendable set of actions for recourse. Instead, we propose a shift of paradigm from recourse via nearest counterfactual explanations to recourse through minimal interventions, shifting the focus from explanations to interventions.
Simulating Performance of ML Systems with Offline Profiling

We advocate that simulation based on offline profiling is a promising approach to better understand and improve the complex ML systems. Our approach uses operation-level profiling and dataflow based simulation to ensure it offers a unified and automated solution for all frameworks and ML models, and is also accurate by considering the various parallelization strategies in a real system.
Semantic Relatedness and Taxonomic Word Embeddings

This paper connects a series of papers dealing with taxonomic word embeddings. It begins by noting that there are different types of semantic relatedness and that different lexical representations encode different forms of relatedness. A particularly important distinction within semantic relatedness is that of thematic versus taxonomic relatedness. Next, we present a number of experiments that analyse taxonomic embeddings that have been trained on a synthetic corpus that has been generated via a random walk over a taxonomy. These experiments demonstrate how the properties of the synthetic corpus, such as the percentage of rare words, are affected by the shape of the knowledge graph the corpus is generated from. Finally, we explore the interactions between the relative sizes of natural and synthetic corpora on the performance of embeddings when taxonomic and thematic embeddings are combined.
Latent Variables on Spheres for Autoencoders in High Dimensions

Variational Auto-Encoder (VAE) has been widely applied as a fundamental generative model in machine learning. For complex samples like imagery objects or scenes, however, VAE suffers from the dimensional dilemma between reconstruction precision that needs high-dimensional latent codes and probabilistic inference that favors a low-dimensional latent space. By virtue of high-dimensional geometry, we propose a very simple algorithm, called Spherical Auto-Encoder (SAE), completely different from existing VAEs to address the issue. SAE is in essence the vanilla autoencoder with spherical normalization on the latent space. We analyze the unique characteristics of random variables on spheres in high dimensions and argue that random variables on spheres are agnostic to various prior distributions and data modes when the dimension is sufficiently high. Therefore, SAE can harness a high-dimensional latent space to improve the inference precision of latent codes while maintain the property of stochastic sampling from priors. The experiments on sampling and inference validate our theoretical analysis and the superiority of SAE.
Deep RL Agent for a Real-Time Action Strategy Game

We introduce a reinforcement learning environment based on Heroic - Magic Duel, a 1 v 1 action strategy game. This domain is non-trivial for several reasons: it is a real-time game, the state space is large, the information given to the player before and at each step of a match is imperfect, and distribution of actions is dynamic. Our main contribution is a deep reinforcement learning agent playing the game at a competitive level that we trained using PPO and self-play with multiple competing agents, employing only a simple reward of $\pm 1$ depending on the outcome of a single match. Our best self-play agent, obtains around $65\%$ win rate against the existing AI and over $50\%$ win rate against a top human player.
Competition for access to mates predicts female-specific ornamentation and polyandry

Sexually selected ornaments are highly variable and the factors that drive variation in ornament expression are not always clear. Rare instances of female-specific ornament evolution (such as in some dance fly species) are particularly puzzling. While some evidence suggests that such rare instances represent straightforward reversals of sexual selection intensity, the distinct nature of trade-offs between ornaments and offspring pose special constraints in females. To examine whether competition for access to mates generally favours heightened ornament expression, we built a phylogeny and conducted a comparative analysis of Empidinae dance fly taxa that display ornate female-specific ornaments. We show that species with more female-biased operational sex ratios in lek-like mating swarms have greater female ornamentation, and in taxa with more ornate females, polyandry is increased. These findings support the hypothesis that ornament diversity in dance flies depends on female receptivity, which is associated with contests for nutritious nuptial gifts provided by males. Moreover, our results suggest that increases in female receptivity lead to higher levels of polyandry and sperm competition among males. The incidence of both heightened pre-mating sexual selection on females and post-mating selection on males contradicts assertions that sex-roles are straightforwardly reversed in dance flies.
Searching for Prosociality in Qualitative Data: Comparing Manual, Closed–Vocabulary, and Open–Vocabulary Methods

Although most people present themselves as possessing prosocial traits, people differ in the extent to which they actually act prosocially in everyday life. Qualitative data that were not ostensibly collected to measure prosociality might contain information about prosocial dispositions that is not distorted by self–presentation concerns. This paper seeks to characterise charitable donors from qualitative data. We compared a manual approach of extracting predictors from participants’ self–described personal strivings to two automated approaches: A summation of words predefined as prosocial and a support vector machine classifier. Although variables extracted by the support vector machine predicted donation behaviour well in the training sample (N = 984), virtually, no variables from any method significantly predicted donations in a holdout sample (N = 496). Raters’ attempts to predict donations to charity based on reading participants’ personal strivings were also unsuccessful. However, raters’ predictions were associated with past charitable involvement. In sum, predictors derived from personal strivings did not robustly explain variation in charitable behaviour, but personal strivings may nevertheless contain some information about trait prosociality. The sparseness of personal strivings data, rather than the irrelevance of open–ended text or individual differences in goal pursuit, likely explains their limited value in predicting prosocial behaviour. © 2020 European Association of Personality Psychology
The Serum Neutrophil Gelatinase-Associated Lipocalin Predicts Early Acute Kidney Injury after Liver Transplantation

Introduction: Acute kidney injury (AKI) following liver transplantation (LT) is a frequent complication and is associated with increased morbidity and mortality. Aim: To investigate whether the levels of serum NGAL are able to predict early occurrence (within the first 48 hours) of the post-LT renal dysfunction. Methods: The study was conducted on 50 recipients transplanted at the Fundeni Clinical Institute between May 2016 and June 2017. Serum NGAL and serum creatinine (sCr) were analyzed before LT, as well as 4 and 24 hours after graft reperfusion. In defining renal failure, the criteria of Kidney Disease Improving Global Outcome (KDIGO) were used. All patients received the same renal sparing regimen of immunosuppression. Results: Twenty-four patients (48%) had early post-LT (<48 hours) renal dysfunction according to the KDIGO criteria. In the AKI group, there was a considerable increase in NGAL values at 4 hours after hepatic reperfusion in comparison with baseline values (p<0.0001), whereas in the group without AKI, the values of NGAL remained about the same (p=0.18). The single independent risk factor for early post-LT AKI occurrence was serum NGAL value 4 hours after hepatic reperfusion. The clinical utility of serum NGAL at 4 h after hepatic reperfusion for AKI prediction was excellent (AUROC 0.981, p=0.0001). Patients receiving a liver with a longer cold ischemia time (>6h) had a significantly higher NGAL serum levels at both 4 and 24h after reperfusion. Conclusion: Early renal dysfunction following LT is frequent (48%) despite using a renal sparing immunosuppression regimen. Serum NGAL at 4 hours after hepatic reperfusion accurately predict AKI early, in the first 48 hours after LT.
Open-Bud Duplicate Loci Are Identified as MML10s, Orthologs of MIXTA-Like Genes on Homologous Chromosomes of Allotetraploid Cotton

The open-bud (ob) mutants in cotton display abnormal flower buds with the stigma and upper anthers exposed before blooming. This characteristic is potentially useful for the efficient production of hybrid seeds. The recessive inheritance pattern of the ob phenotype in allotetraploid cotton is determined by duplicated recessive loci (ob1ob1ob2ob2). In this study, ob1, which is a MIXTA-like MYB gene on chromosome D13 (MML10_Dt), was identified by map-based cloning. In Gossypium barbadense (Gb) acc. 3–79, a single nucleotide polymorphism (SNP) (G/A) at the splice site of the first intron and an 8-bp deletion in the third exon of MML10_Dt were found, which are the causative mutations at the ob1 loci. A 1783-bp deletion that leads to the loss of the third exon and accounts for the causal variation at the ob2 loci was found in MML10_At of Gossypium hirsutum (Gh) acc. TM-1. The ob phenotype results from the combination of these two loss-of-function loci. Genotyping assays showed that the ob1 and ob2 loci appeared after the formation of allotetraploid cotton and were specific for Gb and Gh, respectively. All Gb lines and most Gh cultivars carry the single corresponding mutant alleles. Genome-wide transcriptome analysis showed that some of the MYB genes and genes related to cell wall biogenesis, trichome differentiation, cytokinin signal transduction, and cell division were repressed in the ob mutants, which may lead to suppression of petal growth. These findings should be of value for breeding superior ob lines in cotton.
Contrasting Effects of Adipokines on the Cytokine Production by Primary Human Bronchial Epithelial Cells: Inhibitory Effects of Adiponectin

Background Obesity is associated with an elevated risk of respiratory infections and inflammatory lung diseases. The objective was to investigate (i) the effects of adipokines (adiponectin (APN), leptin, chemerin, and visfatin) on the production of cytokines by unstimulated and poly(I:C)- and TNF-α-activated human primary bronchial epithelial cells (hBECs), (ii) the cells’ expression of the APN receptors (AdipoR1 and AdipoR2), and (iii) the cells' production of APN. Methods The hBECs were isolated from patients undergoing surgery for lung carcinoma. The cells were then cultured with human recombinant adipokines in the absence or presence of TNF-α or poly(I:C) for 24 h. Supernatant levels of cytokines (IL-6, CCL2, CCL5, CCL20, CXCL1, CXCL8) and APN were measured using ELISAs. The mRNA levels of AdipoR1 and AdipoR2 in hBECs were determined using a real-time quantitative PCR. Results Of the four adipokines tested, only APN significantly influenced the basal production and the TNF-α poly(I:C)-induced production of cytokines by hBECs. APN (3-30 µg.ml-1) was associated with greater basal production of IL-6, CCL20, and CXCL8, lower basal production of CCL2 and CXCL1 and no difference in CCL5 production. APN inhibited the poly(I:C)-induced production of these five cytokines and the TNF-α-induced production of CCL2 and CXCL1. AdipoR1 and AdipoR2 were both expressed in hBECs. In contrast to human bronchial explants, isolated hBECs did not produce APN. Conclusions The APN concentrations are abnormally low in obese individuals, and this fall may contribute to the susceptibility to viral lung infections and the severity of these infections in obese individuals.
Assessing Time-Resolved fNIRS for Brain-Computer Interface Applications of Mental Communication

Brain-computer interfaces (BCIs) are becoming increasingly popular as a tool to improve the quality of life of patients with disabilities. Recently, time-resolved functional near-infrared spectroscopy (TR-fNIRS) based BCIs are gaining traction because of their enhanced depth sensitivity leading to lower signal contamination from the extracerebral layers. This study presents the first account of TR-fNIRS based BCI for “mental communication” on healthy participants. Twenty-one (21) participants were recruited and were repeatedly asked a series of questions where they were instructed to imagine playing tennis for “yes” and to stay relaxed for “no.” The change in the mean time-of-flight of photons was used to calculate the change in concentrations of oxy- and deoxyhemoglobin since it provides a good compromise between depth sensitivity and signal-to-noise ratio. Features were extracted from the average oxyhemoglobin signals to classify them as “yes” or “no” responses. Linear-discriminant analysis (LDA) and support vector machine (SVM) classifiers were used to classify the responses using the leave-one-out cross-validation method. The overall accuracies achieved for all participants were 75% and 76%, using LDA and SVM, respectively. The results also reveal that there is no significant difference in accuracy between questions. In addition, physiological parameters [heart rate (HR) and mean arterial pressure (MAP)] were recorded on seven of the 21 participants during motor imagery (MI) and rest to investigate changes in these parameters between conditions. No significant difference in these parameters was found between conditions. These findings suggest that TR-fNIRS could be suitable as a BCI for patients with brain injuries.
Modeling Bainbridge-Ropers Syndrome in Xenopus laevis Embryos

The Additional sex combs-like (ASXL1-3) genes are linked to human neurodevelopmental disorders. The de novo truncating variants in ASXL1-3 proteins serve as the genetic basis for severe neurodevelopmental diseases such as Bohring-Opitz, Shashi-Pena, and Bainbridge-Ropers syndromes, respectively. The phenotypes of these syndromes are similar but not identical, and include dramatic craniofacial defects, microcephaly, developmental delay, and severe intellectual disability, with a loss of speech and language. Bainbridge-Ropers syndrome resulting from ASXL3 gene mutations also includes features of autism spectrum disorder. Human genomic studies also identified missense ASXL3 variants associated with autism spectrum disorder, but lacking more severe Bainbridge-Ropers syndromic features. While these findings strongly implicate ASXL3 in mammalian brain development, its functions are not clearly understood. ASXL3 protein is a component of the polycomb deubiquitinase complex that removes mono-ubiquitin from Histone H2A. Dynamic chromatin modifications play important roles in the specification of cell fates during early neural patterning and development. In this study, we utilize the frog, Xenopus laevis as a simpler and more accessible vertebrate neurodevelopmental model system to understand the embryological cause of Bainbridge-Ropers syndrome. We have found that ASXL3 protein knockdown during early embryo development highly perturbs neural cell fate specification, potentially resembling the Bainbridge-Ropers syndrome phenotype in humans. Thus, the frog embryo is a powerful tool for understanding the etiology of Bainbridge-Ropers syndrome in humans.
Being Smart Is Not Enough: Personality Traits and Vocational Interests Incrementally Predict Intention, Status and Success of Leaders and Entrepreneurs Beyond Cognitive Ability

Three separate studies demonstrate that socio-emotional skills add incremental validity beyond cognitive ability when predicting leadership and entrepreneurship intention, emergence as well as success. Study 1 uses a longitudinal approach and tests the cognitive ability and vocational interests of 231 students to predict their leadership and entrepreneurship intention. It demonstrates that cognitive ability predicts their intention to become a business leader or entrepreneur 2 years in the future. Importantly, the vocational interests “enterprising” and “social” increase this ability-driven prediction of leadership and entrepreneurship intention (ΔR2Lead.Intent. = 15%, ΔR2Entre.Intent. = 9%). Study 2 investigates 123 business leaders and shows that those with higher cognitive ability more likely emerge as top-level leaders, receive more income and get slightly better supervisor-ratings on their performance. The leaders’ Big Five traits (openness, conscientiousness, extraversion, agreeableness, emotional stability) added validity beyond cognitive ability when predicting these criteria (ΔR2Income = 9%, ΔR2Lead.Level = 8%, ΔR2Perform. = 15%). Finally, Study 3 includes 155 participants and demonstrates that cognitive ability predicts a person’s entrepreneurial status but not performance. Additionally, considering the Big Five traits improves the prediction of who becomes an entrepreneur and successfully performs as such (ΔR2Status = 7%, ΔR2Perform. = 18%). Importantly, selected Big Five traits and vocational interests boost the importance of cognitive ability in the field of leadership and entrepreneurship. Concluding, this series of studies suggests that it is the combination of personality traits or interests with cognitive ability which is most powerful when predicting leadership and entrepreneurship intention, emergence and success.
Topical Application of Wogonin Provides a Novel Treatment of Knee Osteoarthritis

Osteoarthritis (OA) is a degenerative joint disease characterized by inflammatory degradation of articular cartilage and subchondral bone. Wogonin, a compound extracted from the plant Scutellaria baicalensis (colloquially known as skullcap), has previously been shown to have direct anti-inflammatory and antioxidative properties. We examined the pain-reducing, anti-inflammatory, and chondroprotective effects of wogonin when applied as a topical cream. We validated the efficacy of delivering wogonin transdermally in a cream using pig ear skin in a Franz diffusion system. Using a surgical mouse model, we examined the severity and progression of OA with and without the topical application of wogonin. Using a running wheel to track activity, we found that mice with wogonin treatment were statistically more active than mice receiving vehicle treatment. OA progression was analyzed using modified Mankin and OARSI scoring and direct quantification of cyst-like lesions at the chondro-osseus junction; in each instance we observed a statistically significant attenuation of OA severity among mice treated with wogonin compared to the vehicle treatment. Immunohistochemistry revealed a significant decrease in protein expression of transforming growth factor β1 (TGF-β1), high temperature receptor A1 (HTRA1), matrix metalloprotease 13 (MMP-13) and NF-κB in wogonin-treated mice, further bolstering the cartilage morphology assessments in the form of a decrease in inflammatory and OA biomarkers.
Genome-Wide Association Study and QTL Meta-Analysis Identified Novel Genomic Loci Controlling Potassium Use Efficiency and Agronomic Traits in Bread Wheat

Potassium use efficiency, a complex trait, directly impacts the yield potential of crop plants. Low potassium efficiency leads to a high use of fertilizers, which is not only farmer unfriendly but also deteriorates the environment. Genome-wide association studies (GWAS) are widely used to dissect complex traits. However, most studies use single-locus one-dimensional GWAS models which do not provide true information about complex traits that are controlled by multiple loci. Here, both single-locus GWAS (MLM) and multi-locus GWAS (pLARmEB, FASTmrMLM, mrMLM, FASTmrEMMA) models were used with genotyping from 90 K Infinium SNP array and phenotype derived from four normal and potassium-stress environments, which identified 534 significant marker-trait associations (MTA) for agronomic and potassium related traits: pLARmEB = 279, FASTmrMLM = 213, mrMLM = 35, MLM = 6, FASTmrEMMA = 1. Further screening of these MTA led to the detection of eleven stable loci: q1A, q1D, q2B-1, q2B-2, q2D, q4D, q5B-1, q5B-2, q5B-3, q6D, and q7A. Moreover, Meta-QTL (MQTL) analysis of four independent QTL studies for potassium deficiency in bread wheat located 16 MQTL on 13 chromosomes. One locus identified in this study (q5B-1) colocalized with an MQTL (MQTL_11 ), while the other ten loci were novel associations. Gene ontology of these loci identified 20 putative candidate genes encoding functional proteins involved in key pathways related to stress tolerance, sugar metabolism, and nutrient transport. These findings provide potential targets for breeding potassium stress resistant wheat cultivars and advocate the advantages of multi-locus GWAS models for studying complex traits.
BCAP Regulates Dendritic Cell Maturation Through the Dual-Regulation of NF-κB and PI3K/AKT Signaling During Infection

The maturation of dendritic cells (DCs) is essential in adaptive immunity. B cell adapter for phosphoinositide 3-kinase (BCAP) has been shown a divergent activities in cell type dependent manner including B cells, NK cells, macrophages, and plasmacytoid DCs (pDCs), however, its role in conventional DCs (cDCs) remains unknown. Here, we report that BCAP negatively regulates Toll-like receptor-induced cDC maturation and inhibits cDCs from inducing antigen-specific T cell responses, thereby weakening the antibacterial adaptive immune responses of mice in a Listeria monocytogenes-infection model. Furthermore, we demonstrate that BCAP simultaneously modulates the activation of the NF-κB and PI3K/AKT signaling by dynamically interacting with, respectively, MyD88 and the p85α subunit of PI3K. Our study thus reveals non-redundant roles for BCAP in regulating cDC maturation and reveals a bilateral signal transduction mechanism.