Miracle-dz/UniFAR-FTUs huggingface dataset:
Facial age cues and emotional expression interact asymmetrically: age cues moderate emotion categorisation

ABSTRACT Facial attributes such as race, sex, and age can interact with emotional expressions; however, only a couple of studies have investigated the nature of the interaction between facial age cues and emotional expressions and these have produced inconsistent results. Additionally, these studies have not addressed the mechanism/s driving the influence of facial age cues on emotional expression or vice versa. In the current study, participants categorised young and older adult faces expressing happiness and anger (Experiment 1) or sadness (Experiment 2) by their age and their emotional expression. Age cues moderated categorisation of happiness vs. anger and sadness in the absence of an influence of emotional expression on age categorisation times. This asymmetrical interaction suggests that facial age cues are obligatorily processed prior to emotional expressions. Finding a categorisation advantage for happiness expressed on young faces relative to both anger and sadness which are negative in valence but different in their congruence with old age stereotypes or structural overlap with age cues suggests that the observed influence of facial age cues on emotion perception is due to the congruence between relatively positive evaluations of young faces and happy expressions.
A fixed viewpoint approach for dense reconstruction of transparent objects

This paper addresses the problem of reconstructing the surface shape of transparent objects. The difficulty of this problem originates from the viewpoint dependent appearance of a transparent object, which quickly makes reconstruction methods tailored for diffuse surfaces fail disgracefully. In this paper, we develop a fixed viewpoint approach for dense surface reconstruction of transparent objects based on refraction of light. We introduce a simple setup that allows us alter the incident light paths before light rays enter the object, and develop a method for recovering the object surface based on reconstructing and triangulating such incident light paths. Our proposed approach does not need to model the complex interactions of light as it travels through the object, neither does it assume any parametric form for the shape of the object nor the exact number of refractions and reflections taken place along the light paths. It can therefore handle transparent objects with a complex shape and structure, with unknown and even inhomogeneous refractive index. Experimental results on both synthetic and real data are presented which demonstrate the feasibility and accuracy of our proposed approach.
Development of a Virtual Collision Sensor for Industrial Robots

Collision detection is a fundamental issue for the safety of a robotic cell. While several common methods require specific sensors or the knowledge of the robot dynamic model, the proposed solution is constituted by a virtual collision sensor for industrial manipulators, which requires as inputs only the motor currents measured by the standard sensors that equip a manipulator and the estimated currents provided by an internal dynamic model of the robot (i.e., the one used inside its controller), whose structure, parameters and accuracy are not known. The collision detection is achieved by comparing the absolute value of the current residue with a time-varying, positive-valued threshold function, including an estimate of the model error and a bias term, corresponding to the minimum collision torque to be detected. The value of such a term, defining the sensor sensitivity, can be simply imposed as constant, or automatically customized for a specific robotic application through a learning phase and a subsequent adaptation process, to achieve a more robust and faster collision detection, as well as the avoidance of any false collision warnings, even in case of slow variations of the robot behavior. Experimental results are provided to confirm the validity of the proposed solution, which is already adopted in some industrial scenarios.
Tocotrienols Stimulate Insulin Secretion of Rat Pancreatic Isolated Islets in a Dynamic Culture.

BACKGROUND Tocotrienols (T3) are the naturally occurring vitamin E derivatives that possess antioxidant properties and therapeutic potential in diabetic complications. The bioactivities of the derivatives are determined by the number and arrangement of methyl substitution on the structure. OBJECTIVE The objective of this study was to determine the effects of T3 derivatives, σ-T3, γ-T3 and α-T3 on insulin secretion of rat pancreatic islets in a dynamic culture. METHOD Pancreatic islets isolated from male Wistar rats were treated with T3 for 1 h at 37°C in a microfluidic system with continuous operation that provided a stable cell culture environment. Glucose (2.8 mM and 16.7 mM, as basal and stimulant, respectively) and potassium chloride (KCl) (30 mM) were added to the treatment in calcium free medium. The supernatant was collected for insulin measurements. RESULTS Short-term exposure (1 h) of σ-T3 to β cells in the stimulant glucose condition significantly potentiated insulin secretion in a dose-dependent manner. γ-T3 and α-T3 also displayed dosedependent effect but were less effective in the activation of insulin secretion. Essentially, KCl, a pancreatic β cell membrane depolarizing agent, added into the treatment further enhanced the insulin secretion of σ-T3, γ-T3 and α-T3 with ED50 values of 504, 511 and 588 µM, respectively. CONCLUSION The findings suggest the potential of σ-T3 in regulating glucose-stimulated insulin secretion (GSIS) in response to the intracellular calcium especially in the presence of KCl.
Linking Light Exposure and Subsequent Sleep: A Field Polysomnography Study in Humans

Abstract Study objectives To determine the effect of light exposure on subsequent sleep characteristics under ambulatory field conditions. Methods Twenty healthy participants were fitted with ambulatory polysomnography (PSG) and wrist-actigraphs to assess light exposure, rest–activity, sleep quality, timing, and architecture. Laboratory salivary dim-light melatonin onset was analyzed to determine endogenous circadian phase. Results Later circadian clock phase was associated with lower intensity (R2 = 0.34, χ2(1) = 7.19, p < . 01), later light exposure (quadratic, controlling for daylength, R2 = 0.47, χ2(3) = 32.38, p < . 0001), and to later sleep timing (R2 = 0.71, χ2(1) = 20.39, p < . 0001). Those with later first exposure to more than 10 lux of light had more awakenings during subsequent sleep (controlled for daylength, R2 = 0.36, χ2(2) = 8.66, p < . 05). Those with later light exposure subsequently had a shorter latency to first rapid eye movement (REM) sleep episode (R2 = 0.21, χ2(1) = 5.77, p < . 05). Those with less light exposure subsequently had a higher percentage of REM sleep (R2 = 0.43, χ2(2) = 13.90, p < . 001) in a clock phase modulated manner. Slow-wave sleep accumulation was observed to be larger after preceding exposure to high maximal intensity and early first light exposure (p < .05). Conclusions The quality and architecture of sleep is associated with preceding light exposure. We propose that light exposure timing and intensity do not only modulate circadian-driven aspects of sleep but also homeostatic sleep pressure. These novel ambulatory PSG findings are the first to highlight the direct relationship between light and subsequent sleep, combining knowledge of homeostatic and circadian regulation of sleep by light. Upon confirmation by interventional studies, this hypothesis could change current understanding of sleep regulation and its relationship to prior light exposure. Clinical trial details This study was not a clinical trial. The study was ethically approved and nationally registered (NL48468.042.14).
Enhanced precision in the analysis of randomized trials with ordinal outcomes

We present a general method for estimating the effect of a treatment on an ordinal outcome in randomized trials. The method is robust in that it does not rely on the proportional odds assumption. Our estimator leverages information in prognostic baseline variables, and has all of the following properties: (i) it is consistent; (ii) it is locally efficient; (iii) it is guaranteed to have equal or better asymptotic precision than both the inverse probability‐weighted and the unadjusted estimators. To the best of our knowledge, this is the first estimator of the causal relation between a treatment and an ordinal outcome to satisfy these properties. We demonstrate the estimator in simulations based on resampling from a completed randomized clinical trial of a new treatment for stroke; we show potential gains of up to 39% in relative efficiency compared to the unadjusted estimator. The proposed estimator could be a useful tool for analyzing randomized trials with ordinal outcomes, since existing methods either rely on model assumptions that are untenable in many practical applications, or lack the efficiency properties of the proposed estimator. We provide R code implementing the estimator.
Honokiol suppresses proliferation and induces apoptosis via regulation of the miR-21/PTEN/PI3K/AKT signaling pathway in human osteosarcoma cells

Honokiol (HNK) is a small biphenolic compound, which exerts antineoplastic effects in various types of cancer. However, the mechanism underlying the antitumor effects of HNK in osteosarcoma (OS) cells is not yet fully understood. Emerging evidence has indicated that microRNAs (miRNAs/miRs) serve key roles in numerous pathological processes, including cancer. It has previously been reported that Chinese medicinal herbs harbor anticancer properties via modulating miRNA expression. Therefore, the present study aimed to determine whether HNK could suppress OS cell growth by regulating miRNA expression. The 3-(4,5-dimethylthiazol-2-yl)-2,5-diphenyltetrazolium bromide (MTT) assay and flow cytometric analysis were used to evaluate the cell proliferation and apoptosis in human OS cells after treatment with HNK, respectively. The results demonstrated that HNK inhibits proliferation and induces apoptosis of human OS cells in a dose-dependent manner. Furthermore, HNK-induced apoptosis was characterized by upregulation of proapoptotic proteins, including cleaved-caspase-3, cleaved-poly (ADP-ribose) polymerase and B-cell lymphoma 2 (Bcl-2)-associated X protein, and downregulation of the anti-apoptotic protein Bcl-2. Reverse transcription-quantitative polymerase chain reaction (RT-qPCR) verified that HNK was able to induce aberrant expression of miRNAs in human OS cells, and miR-21 was one of the miRNAs that was most significantly downregulated. To further investigate miR-21 function, the present study validated that HNK reduces miR-21 levels in a dose-dependent manner. In addition, restoration of miR-21 expression abrogated the suppressive effects of HNK on OS cells. Luciferase assay and western blot analysis identified that miR-21 inhibits the expression of phosphatase and tensin homolog (PTEN) by directly targeting its 3′-UTR. Notably, HNK was able to suppress the phosphoinositide 3-kinase (PI3K)/protein kinase B (AKT) signaling pathway; however, it was reactivated by miR-21 overexpression. Taken together, these data indicated that HNK may inhibit proliferation and induce apoptosis of human OS cells by modulating the miR-21/PTEN/PI3K/AKT signaling pathway. Therefore, miR-21 may be considered a potential therapeutic target for the treatment of osteosarcoma with HNK.
The functions and value of reminiscence for older adults in long-term residential care facilities

ABSTRACT For the many older adults living in long-term care facilities, the ability to connect with others, as well as with one’s own personal past, may be of particular value. Reflecting on the past and sharing reminiscences with others serves different psychosocial functions in various settings. This study examined the functions of reminiscence for long-term care residents in the United States (Mage = 86.5) by addressing the self-reported frequency of reminiscence, the counterparties involved, the overall purpose and value of reminiscence, and the relation to residents’ mental health and well-being. Results demonstrated that although some functions of reminiscence were comparable to those found in community-dwelling older adults, others were unique to the long-term care setting. Residents were most likely to reminisce alone and they found the experience enjoyable. They reported engaging in and enjoying reminiscence with family more than with fellow residents, and a subset desired increased opportunities to share memories with healthcare providers. Residents with lower morale and more depressive symptoms were more likely to engage in unhealthy styles of reminiscence. These findings suggest that interventions shaping reminiscence encounters may have positive outcomes for long-term care residents.
Functional Gradient Boosting based on Residual Network Perception

Residual Networks (ResNets) have become state-of-the-art models in deep learning and several theoretical studies have been devoted to understanding why ResNet works so well. One attractive viewpoint on ResNet is that it is optimizing the risk in a functional space by combining an ensemble of effective features. In this paper, we adopt this viewpoint to construct a new gradient boosting method, which is known to be very powerful in data analysis. To do so, we formalize the gradient boosting perspective of ResNet mathematically using the notion of functional gradients and propose a new method called ResFGB for classification tasks by leveraging ResNet perception. Two types of generalization guarantees are provided from the optimization perspective: one is the margin bound and the other is the expected risk bound by the sample-splitting technique. Experimental results show superior performance of the proposed method over state-of-the-art methods such as LightGBM.
Intrinsic functional network organization in high-functioning adolescents with autism spectrum disorder

Converging theories and data suggest that atypical patterns of functional and structural connectivity are a hallmark neurobiological feature of autism. However, empirical studies of functional connectivity, or, the correlation of MRI signal between brain regions, have largely been conducted during task performance and/or focused on group differences within one network [e.g., the default mode network (DMN)]. This narrow focus on task-based connectivity and single network analyses precludes investigation of whole-brain intrinsic network organization in autism. To assess whole-brain network properties in adolescents with autism, we collected resting-state functional connectivity MRI (rs-fcMRI) data from neurotypical (NT) adolescents and adolescents with autism spectrum disorder (ASD). We used graph theory metrics on rs-fcMRI data with 34 regions of interest (i.e., nodes) that encompass four different functionally defined networks: cingulo-opercular, cerebellar, fronto-parietal, and DMN (Fair etal., 2009). Contrary to our hypotheses, network analyses revealed minimal differences between groups with one exception. Betweenness centrality, which indicates the degree to which a seed (or node) functions as a hub within and between networks, was greater for participants with autism for the right lateral parietal (RLatP) region of the DMN. Follow-up seed-based analyses demonstrated greater functional connectivity in ASD than NT groups between the RLatP seed and another region of the DMN, the anterior medial prefrontal cortex. Greater connectivity between these regions was related to lower ADOS (Autism Diagnostic Observation Schedule) scores (i.e., lower impairment) in autism. These findings do not support current theories of underconnectivity in autism, but, rather, underscore the need for future studies to systematically examine factors that can influence patterns of intrinsic connectivity such as autism severity, age, and head motion.
A Two-Echelon Cooperated Routing Problem for a Ground Vehicle and Its Carried Unmanned Aerial Vehicle

In this paper, a two-echelon cooperated routing problem for the ground vehicle (GV) and its carried unmanned aerial vehicle (UAV) is investigated, where the GV travels on the road network and its UAV travels in areas beyond the road to visit a number of targets unreached by the GV. In contrast to the classical two-echelon routing problem, the UAV has to launch and land on the GV frequently to change or charge its battery while the GV is moving on the road network. A new 0–1 integer programming model is developed to formulate the problem, where the constraints on the spatial and temporal cooperation of GV and UAV routes are included. Two heuristics are proposed to solve the model: the first heuristic (H1) constructs a complete tour for all targets and splits it by GV routes, while the second heuristic (H2) constructs the GV tour and assigns UAV flights to it. Random instances with six different sizes (25–200 targets, 12–80 rendezvous nodes) are used to test the algorithms. Computational results show that H1 performs slightly better than H2, while H2 uses less time and is more stable.
Biological evaluation and energetic analyses of novel GSK‐3β inhibitors

Glycogen synthase kinase‐3 beta (GSK‐3β) is involved in multiple signaling pathways. Consistent with its critical roles in normal cells, abnormalities in GSK‐3β activity have been implicated in diabetes, heart disease, Parkinson disease, and Alzheimer's disease. In this study, a series of new scaffolds of small molecule inhibitors of GSK‐3β were identified by virtual screening and bioassay. Candidates that adhere to drug‐like criteria from a virtual library of compounds were tested using computational docking studies. Twenty selected compounds were tested, which led to the discovery of two hits. Compound 14 (IC50 = 8.48 µM) and compound 19 (IC50 = 2.19 µM) were identified with high affinity. Molecular dynamics (MD) simulations, in conjunction with molecular mechanics/Poisson‐Boltzmann surface area binding free‐energy analysis, were employed to gain insight into the binding modes and energetics of GSK‐3β inhibitors. The detailed analysis of molecular dynamics results shows that Ile62, Val70, Tyr134, and Leu188 in GSK‐3β are key residues responsible to the binding of compound 14 and compound 19. Importantly, our results also validated this combined virtual screening and biophysical technique approach to discovery kinase inhibitors, which may be applied for future inhibitor discovery work for GSK‐3β.
Enterotoxin production and antimicrobial susceptibility in Staphylococci isolated from traditional raw milk cheeses in Serbia

ABSTRACT This study was undertaken to determine the prevalence of coagulase positive staphylococci (CPS) by examining a total of 71 raw milk cheeses. Additionally, enterotoxigenicity, antimicrobial susceptibility and the presence of mecA and mecC genes in the staphylococcal isolates were investigated. The isolation and enumeration procedure of CPS followed the International Organization for Standardization (ISO) standard. The presumptive staphylococci were identified by matrix-assisted laser desorption ionization-time of flight mass spectrometry (MALDI-TOF MS) using the VITEK MS system. VIDAS® Staph enterotoxin II assay was used for the detection of classical enterotoxins. Antimicrobial susceptibility testing (AST) was accomplished performing the disk diffusion method. All suspected methicillin resistant staphylococci were investigated for the presence of mecA and mecC genes by PCR assay. A high prevalence (87.32%) of CPS was detected in the cheeses at contamination levels up to 5.58 log CFU g−1. Among 47 staphylococcal isolates screened for enterotoxin production, only one isolate, identified as S. hyicus, was confirmed as being enterotoxigenic. Resistance to penicillin (63.70%) was the most common resistance among the tested Staphylococcus aureus isolates. The dominant phenotypic resistance patterns in coagulase negative staphylococci (CNS) were resistance to ofloxacin and fusidic acid. All CNS isolates were susceptible to the clinically important antibiotics clindamycin, chloramphenicol, gentamicin, linezolid, rifampicin and trimethoprim-sulfamethoxazole. The mecA and mecC genes were not detected. To the best of our knowledge, this is the first study concerning evaluation of the presence of methicillin resistant staphylococci (MRS) in dairy products in Serbia.
New onset or worsening of psoriasis following biologic therapy: A case series

Biologic therapies may cause so-called “paradoxical side-effects,” that is, the onset or exacerbation of new symptoms/diseases for which biological treatment should be effective. Among these, psoriatic skin lesions have been described. We report a case series of ten patients with either new onset (seven cases) or worsening (three cases) of psoriasis occurring during a biologic therapy. Six patients were receiving a biologic monotherapy, while four patients were in combination treatment with methotrexate (MTX). Psoriasis remission was observed in two patients who discontinued biologic therapy. In the six patients in whom biologic therapy was not discontinued, a complete disappearance or a partial improvement of skin lesions was achieved following topic steroid therapy in two patients and three patients, respectively. In the remaining patient, psoriasis developed during Adalimumab monotherapy, which completely disappeared when the Infliximab and MTX combination was started. The potential pathogenetic mechanisms were shortly reviewed.
Low Inter-Annotator Agreement = An Ill-Defined Problem?

nnotation tasks where the inter-annotator agreement is low are usually considered ill-defined and not worth attention. Such tasks are also considered unsuitable for algorithmic solution and for evaluation of computer programs that aim at solving them. However, there is a lot of problems (not only) in the natural language processing field that are practically defined and do have this nature, and we need computer programs that are able to solve them. The paper illustrates such problems on particular examples and suggests methodology that will enable training and evaluating tools using data with low inter-annotator agreement.
Information Theoretic Analysis of LDS Scheme

In this paper, the capacity region of Low Density Signature Multiple Access Channel (LDS-MAC) is calculated through information theoretic analysis. LDS Code Division Multiple Access (LDS-CDMA) uses spreading sequences of low density for spreading the data symbols in time domain. This technique benefits from a less complex Multiuser Detector (MUD) compared to conventional CDMA with optimum MUD; while keeping the performance close to the single user scenario for up to 200% loaded conditions. Also evaluated is the effect of different factors on the capacity of LDS MAC.