Miracle-dz/UniFAR-FTUs huggingface dataset:
A preference to learn from successful rather than common behaviours in human social dilemmas

Human cooperation is often claimed to be special and requiring explanations based on gene–culture coevolution favouring a desire to copy common social behaviours. If this is true, then individuals should be motivated to both observe and copy common social behaviours. Previous economic experiments, using the public goods game, have suggested individuals' desire to sacrifice for the common good and to copy common social behaviours. However, previous experiments have often not shown examples of success. Here we test, on 489 participants, whether individuals are more motivated to learn about, and more likely to copy, either common or successful behaviours. Using the same social dilemma and standard instructions, we find that individuals were primarily motivated to learn from successful rather than common behaviours. Consequently, social learning disfavoured costly cooperation, even when individuals could observe a stable, pro-social level of cooperation. Our results call into question explanations for human cooperation based on cultural evolution and/or a desire to conform with common social behaviours. Instead, our results indicate that participants were motivated by personal gain, but initially confused, despite receiving standard instructions. When individuals could learn from success, they learned to cooperate less, suggesting that human cooperation is maybe not so special after all.
Traditional and Emerging Use-Cases for Machine Translation

Despite a few remaining naysayers, Machine Translation (MT) is being used by many people now as a productivity tool, with demonstrable success. There is already a wide variety of use-cases, but more are emerging where MT is the only solution. This paper presents the case for MT, describes its impact on the translator, and demonstrates a need for customisable levels of quality rather than a 'one size fits all' solution.
Rapid developments in rapid prototyping

Report from a recent conference held in Italy and organised by the Rapid Prototyping Research Group at the University of Nottingham. Papers were presented on a wide variety of subjects including stereolithography, selective laser sintering, laser forming, fused deposition modelling, three‐dimensional printing, CAD and data transfer and rapid tooling. Tooling was one of the key topics during the three‐day event.
Criteria for the evaluation of linear two-port stability using two geometrically derived parameters

Two geometrically derived stability parameters, µ′ (or µ) and ν′(or ν), are used to analyze the stability of a two-port network. The magnitudes of both µ′ (or µ) and ν′ (or ν) parameters determine geometrical relations between the stability circle and the unit Smith chart in the ΓS (or ΓL) plane. |µ′| (or |µ|) is defined as the minimum distance from the stability circle to the origin of the unit Smith chart in the ΓS (or ΓL) plane, while |ν′|(or |ν|) is defined as the maximum distance. Moreover, the signs of ν′ (or ν) and µ′ (or µ) parameters determine which region of the stability circle is stable (inside or outside) and whether the stable region includes the origin of the Smith chart, respectively. There are totally 12 situations between the stability circle and the unit Smith chart in the ΓS (or ΓL) plane by using µ′ (or µ) and ν′ (or ν) parameters. This paper classifies 12 situations in the ΓS plane and also presents the corresponding practical two-port networks.
Efficient frequency-domain modeling and circuit simulation of transmission lines

In this paper we describe an algorithm for efficient SPICE-level simulation of transmission lines with arbitrary scattering parameter descriptions. That is, the line can be represented in the form of a frequency-domain model or a table of measured frequency-domain data. Our approach initially uses a forced stable decade-by-decade l/sub 2/ minimization approach to construct a sum of rational functions approximation, but the approximation has dozens of poles and zeros. This unnecessarily high-order model is then reduced using a guaranteed stable model order reduction scheme based on balanced realizations. Once the reduced-order model is derived, it can be combined with the transmission line's inherent delay to generate an impulse response. Finally, following what is now a standard approach, the impulse response can be efficiently incorporated in a circuit simulator using recursive convolution. An example of a transmission line with skin-effect is examined to both demonstrate the effectiveness of the approach and to show its generality. >
Can People Sleep Too Much? Effects of Extended Sleep Opportunity on Sleep Duration and Timing

Many people are concerned about whether they are getting “enough” sleep, and if they can “sleep too much. ” These concerns can be approached scientifically using experiments probing long-term (i.e., multi-night) sleep homeostatic processes, since homeostatic processes move the system toward its physiological setpoint (i.e., between “not enough” and “too much”). We analyzed sleep data from two human studies with sleep opportunities much longer than people usually stay in bed (i.e., conditions in which sleep homeostatic responses could be documented): sleep opportunities were 14–16 h per day for 3–28 days. Across the nights of the extended sleep opportunities, total sleep duration, Rapid Eye Movement (REM) sleep duration and non-REM sleep durations decreased and sleep latency increased. Multiple nights were required to reach approximately steady-state values. These results suggest a multi-day homeostatic sleep process responding to self-selected insufficient sleep duration prior to the study. Once steady state-values were reached, there were large night-to-night variations in total sleep time and other sleep metrics. Our results therefore answer these concerns about sleep amount and are important for understanding the basic physiology of sleep and for two sleep-related topics: (i) the inter-individual and intra-individual variability are relevant to understanding “normal” sleep patterns and for people with insomnia and (ii) the multiple nights of sleep required for recovery from insufficient sleep from self-selected sleep loss is important for public health and other efforts for reducing the adverse effects of sleep loss on multiple areas of physiology.
Activin and BMP Signaling Activity Affects Different Aspects of Host Anti-Nematode Immunity in Drosophila melanogaster

The multifaceted functions ranging from cellular and developmental mechanisms to inflammation and immunity have rendered TGF-ß signaling pathways as critical regulators of conserved biological processes. Recent studies have indicated that this evolutionary conserved signaling pathway among metazoans contributes to the Drosophila melanogaster anti-nematode immune response. However, functional characterization of the interaction between TGF-ß signaling activity and the mechanisms activated by the D. melanogaster immune response against parasitic nematode infection remains unexplored. Also, it is essential to evaluate the precise effect of entomopathogenic nematode parasites on the host immune system by separating them from their mutualistic bacteria. Here, we investigated the participation of the TGF-ß signaling branches, activin and bone morphogenetic protein (BMP), to host immune function against axenic or symbiotic Heterorhabditis bacteriophora nematodes (parasites lacking or containing their mutualistic bacteria, respectively). Using D. melanogaster larvae carrying mutations in the genes coding for the TGF-ß extracellular ligands Daw and Dpp, we analyzed the changes in survival ability, cellular immune response, and phenoloxidase (PO) activity during nematode infection. We show that infection with axenic H. bacteriophora decreases the mortality rate of dpp mutants, but not daw mutants. Following axenic or symbiotic H. bacteriophora infection, both daw and dpp mutants contain only plasmatocytes. We further detect higher levels of Dual oxidase gene expression in dpp mutants upon infection with axenic nematodes and Diptericin and Cecropin gene expression in daw mutants upon infection with symbiotic nematodes compared to controls. Finally, following symbiotic H. bacteriophora infection, daw mutants have higher PO activity relative to controls. Together, our findings reveal that while D. melanogaster Dpp/BMP signaling activity modulates the DUOX/ROS response to axenic H. bacteriophora infection, Daw/activin signaling activity modulates the antimicrobial peptide and melanization responses to axenic H. bacteriophora infection. Results from this study expand our current understanding of the molecular and mechanistic interplay between nematode parasites and the host immune system, and the involvement of TGF-ß signaling branches in this process. Such findings will provide valuable insight on the evolution of the immune role of TGF-ß signaling, which could lead to the development of novel strategies for the effective management of human parasitic nematodes.
Urine β2-Microglobulin and Retinol-Binding Protein and Renal Disease Progression in IgA Nephropathy

Background: Tubulointerstitial involvement has been reported to have a decisive influence on the progression of IgA nephropathy (IgAN). High levels of urine β2-microglobulin (β2-MG) and retinol-binding protein (RBP) were observed in patients with IgAN with tubulointerstitial lesions. However, their roles in disease progression remain unclear. This study aimed to evaluate the associations of urine β2-MG and RBP with the progression of IgAN. Methods: We retrospectively investigated a cohort of 2,153 patients with IgAN. Clinical and pathological features, outcomes, and urine β2-MG, and RBP at the time of biopsy were collected. The associations, of urine β2-MG and RBP with the composite renal outcome, defined as a decline in estimated glomerular filtration rate (eGFR) of ≥50% from baseline or end-stage renal disease (ESRD), were examined using restricted cubic splines and the Cox proportional hazards models. Results: During a median follow-up of 20.40 months, 140 (6.50%) patients reached the composite renal outcomes. Restricted cubic splines showed that patients with higher urinary β2-MG and RBP levels had worse renal outcomes. The Cox regression analysis revealed that urine β2-MG and RBP were associated with a risk of the composite renal outcome in the multivariate adjusted model [+1 SD for log β2-MG, hazard ratio (HR) = 1.462, 95% CI: 1.136–1.882, p = 0.003; +1 SD for log RBP, HR = 1.972, 95% CI: 1.486–2.617, p = 0.001]. The associations were detectable within patients with baseline eGFR <90 ml/min/1.73 m2 (+1 SD for log β2-MG, HR = 1.657, 95% CI: 1.260–2.180, p < 0.001; +1 SD for log RBP, HR = 1.618, 95% CI: 1.199–2.183, p = 0.002), but not among patients with eGFR ≥90 ml/min/1.73 m2. Conclusion: Higher levels of urine β2-MG and RBP were independent risk factors for renal disease progression in IgAN.
From Tokenization to Self-Supervision: Building a High-Performance Information Extraction System for Chemical Reactions in Patents

Chemical reactions and experimental conditions are fundamental information for chemical research and pharmaceutical applications. However, the latest information of chemical reactions is usually embedded in the free text of patents. The rapidly accumulating chemical patents urge automatic tools based on natural language processing (NLP) techniques for efficient and accurate information extraction. This work describes the participation of the Melax Tech team in the CLEF 2020—ChEMU Task of Chemical Reaction Extraction from Patent. The task consisted of two subtasks: (1) named entity recognition to identify compounds and different semantic roles in the chemical reaction and (2) event extraction to identify event triggers of chemical reaction and their relations with the semantic roles recognized in subtask 1. To build an end-to-end system with high performance, multiple strategies tailored to chemical patents were applied and evaluated, ranging from optimizing the tokenization, pre-training patent language models based on self-supervision, to domain knowledge-based rules. Our hybrid approaches combining different strategies achieved state-of-the-art results in both subtasks, with the top-ranked F1 of 0.957 for entity recognition and the top-ranked F1 of 0.9536 for event extraction, indicating that the proposed approaches are promising.
Fairness constraint of Fuzzy C-means Clustering improves clustering fairness

Fuzzy C-Means (FCM) clustering is a classic clustering algorithm, which is widely used in the real world. Despite the distinct advantages of FCM algorithm, whether the usage of fairness constraint in the FCM could improve clustering fairness remains fully elusive. By introducing a novel fair loss term into the objective function, a Fair Fuzzy C-Means (FFCM) algorithm was proposed in this current study. We proved that the membership value was constrained by distance and fairness in the meantime during the optimization process in the proposed objective function. By studying the Fuzzy C-Means Clustering with fairness constraint problem and proposing a fair fuzzy C-means method, this study provided mechanism understanding in achieving the fairness constraint in Fuzzy C-Means clustering and bridged up the gap of fair fuzzy clustering.
Self-sensing control as applied to a PZT stack actuator used as a micropositioner

Recently, more attention has been focused on improving open-loop performance characteristics of smart actuator materials. The impetus in pursuing this course of research is reducing the need for oftentimes costly and obtrusive independent sensors used for feedback to the actuator. Self-sensing actuation is a control technique that can be applied to many smart materials including piezoceramics. It involves extracting a sensing signal from the actuating material by use of a bridge circuit, then properly feeding this signal back to improve the actuator's performance. The research presented in this paper is concerned with the feasibility of applying this technique to a soft PZT stacked actuator used as a micropositioner. The result of applying this control technique was a reduction of the micropositioner's decay time from over 1 ms to under 0.3 ms. A major contributor to the success of this research was the insertion of a nonlinear capacitive element in the self-sensing bridge which negated the nonlinear effects of the PZT stack thus enabling an increase in the self-sensing signal to noise ratio.
Sibling, Peer, and Cyber Bullying Among Children and Adolescents: Co-occurrence and Implications for Their Adjustment

Bullying across the sibling, peer, and cyber context has consistently been associated with a range of long-term health and well-being consequences for children and adolescents. Although research examining different bullying forms simultaneously in the same study are emerging, it remains unclear to what extend sibling, peer, and cyber bullying co-occur and in what ways they are associated. Moreover, previous work has demonstrated that children and adolescents who experience multiple forms of victimization are at a particular risk of adverse outcomes. However, whether different constellations of co-occurring bullying forms have differential impacts has not yet been investigated sufficiently. The aim of the present study was to examine the frequencies of isolated and co-occurring sibling, peer, and cyber bullying as well as to explore their independent and cumulative relationships with child adjustment. This study was based on a sample of 329 children and adolescents aged between 9 and 15. Bullying experiences across the sibling, peer, and cyber context in the previous 6 months were assessed via self-report. Youth further reported on emotional problems, conduct problems, sleep problems, and academic achievement via an online questionnaire. Sibling, peer, and cyber bullying were uniquely associated with child outcomes. A cumulative relationship between bullying victimization across contexts and emotional problems, conduct problems, and sleep problems could be identified, while bullying perpetration across contexts was only linked to more conduct problems in a cumulative manner. The findings have important practical implications arguing for the adoption of a holistic approach toward bullying in prevention and intervention.
Case Report: First Case of Cefotaxime-Sulbactam-Induced Acute Intravascular Hemolysis in a Newborn With ABO Blood Type Incompatibility by the Mechanism of Non-Immunologic Protein Adsorption

Background ABO blood type incompatibility hemolytic disease of newborn (ABO-HDN) and drug-induced immune hemolytic anemia (DIIHA) due to non-immunologic protein adsorption (NIPA) mainly cause extravascular hemolysis. All the reported severe DIIHA were caused by drug-induced antibodies, and rare report of acute intravascular hemolysis was caused by the NIPA mechanism or ABO-HDN. Case presentation We report the first case of acute intravascular hemolysis induced by cefotaxime sodium - sulbactam sodium (CTX - SBT) in a case of ABO-HDN which resulted in death at 55 h after birth. The mother’s blood type was O and RhD-positive, and the newborn’s blood type was B and RhD-positive. No irregular red blood cell (RBC) antibodies or drug-dependent antibodies related to CTX or SBT was detected in the mother’s plasma and the plasma or the RBC acid eluent of the newborn. Before the newborn received CTX - SBT treatment, the result of direct antiglobulin test (DAT) was negative while anti-B was positive (2 +) in both plasma and acid eluent. After the newborn received CTX - SBT treatment, the results of DAT for anti-IgG and anti-C3d were both positive, while anti-B was not detected in plasma, but stronger anti-B (3 +) was detected in acid eluent. In vitro experiments confirmed that NIPA of SBT promoted the specific binding of maternal-derived IgG anti-B to B antigen on RBCs of the newborn, thereby inducing acute intravascular hemolysis. Conclusion The NIPA effect of SBT promoted the specific binding of mother-derived IgG anti-B in newborn’s plasma to the newborn’s RBC B antigens and formed an immune complex, and then activated complement, which led to acute intravascular hemolysis. Drugs such as SBT with NIPA effect should not be used for newborns with HDN.
Multi-task Actor-Critic with Knowledge Transfer via a Shared Critic

Multi-task actor-critic is a learning paradigm proposed in the literature to improve the learning eﬃciency of multiple actor-critics by sharing the learned policies across tasks while the reinforcement learning progresses online. However, existing multi-task actor-critic algorithms can only handle reinforcement learning tasks within the same problem domain, they may fail in cases where tasks possessing diverse state-action spaces. Taking this cue, in this paper, we embark a study on multi-task actor-critic with knowledge transfer via a share critic to enable the multi-task learning of actor-critic in heterogeneous state-action environments. Further, for eﬃcient learning of the proposed multi-task actor-critic, a new formula for calculating the gradient of the actor network is also presented. To evaluate the performance of our approach, comprehensive empirical studies on continuous robotic tasks with diﬀerent numbers of links. The experimental results conﬁrmed the eﬀectiveness of the proposed multi-task actor-critic algorithm.
Slice-sampling based 3D Object Classification

Multiview-based 3D object detection achieved great success in the past years. However, for some complex models with complex inner structures, the performances of these methods are not satisfactory. This paper provides a method based on slide sampling for 3D object classiﬁcation. First, we slice and sample the model from the diﬀerent depths and directions to get the model’s features. Then, a deep neural network designed based on the attention mechanism is used to classify the input data. The experiments show that the performance of our method is competitive on ModelNet. Moreover, for some special models with simple surfaces and complex inner structures, the performance of our method is outstanding and stable.
Gut Microbial Dysbiosis Associated with Type 2 Diabetes Aggravates Acute Ischemic Stroke

We demonstrated an additive effect of type 2 diabetes (T2D) and acute ischemic stroke (AIS) on AIS with T2D (AIS_T2D) patient gut microbiota dysbiosis, and gut dysbiosis associated with T2D was positively correlated with stroke severity in AIS patients. Through animal experiments, we found that cerebral injury was exacerbated by fecal microbiota transplantation from T2D patients compared with that from healthy controls, which was associated with a reduction in short-chain fatty acid (SCFA)-producing bacteria. ABSTRACT Type 2 diabetes (T2D) is an independent risk factor for acute ischemic stroke (AIS), but the underlying mechanisms remain elusive. Because the gut microbiota plays a causal role in both T2D and AIS, we wondered whether gut dysbiosis in T2D aggravates stroke progression. We recruited 35 T2D, 90 AIS, 60 AIS with T2D (AIS_T2D) patients, and 55 healthy controls and found that AIS and T2D had an additive effect on AIS_T2D patient gut dysbiosis by exhibiting the largest difference from the heathy controls. In addition, we found that the degree of gut dysbiosis associated with T2D was positively correlated with the National Institutes of Health Stroke Scale (NIHSS), modified Rankin score (mRS), and Essen stroke risk score in patients with AIS, including AIS and AIS_T2D patients. Compared with mice colonized with gut microbiota from healthy controls poststroke modeling, germfree (GF) mice colonized with gut microbiota from T2D patients showed exacerbated cerebral injury and impaired gut barrier function. Specifically, exacerbated brain injury and gut barrier dysfunction in T2D-treated GF mice were significantly associated with a reduction in short-chain fatty acid (SCFA)-producing bacteria. Our study showed that T2D and AIS have an additive effect on AIS_T2D patient gut microbiota dysbiosis. T2D-associated gut microbiota dysbiosis is associated with stroke severity in AIS patients and aggravates stroke progression in mice. IMPORTANCE We demonstrated an additive effect of type 2 diabetes (T2D) and acute ischemic stroke (AIS) on AIS with T2D (AIS_T2D) patient gut microbiota dysbiosis, and gut dysbiosis associated with T2D was positively correlated with stroke severity in AIS patients. Through animal experiments, we found that cerebral injury was exacerbated by fecal microbiota transplantation from T2D patients compared with that from healthy controls, which was associated with a reduction in short-chain fatty acid (SCFA)-producing bacteria. This study provided a novel view that links T2D and AIS through gut microbial dysbiosis.