Miracle-dz/UniFAR-FTUs huggingface dataset:
Immunostimulatory activity of Pichia kluyveri, Hanseniaspora uvarum, Candida intermedia, Saccharomyces boulardii and their derivatives on RAW 264.7 macrophages

Yeasts are a group of microorganisms with structural and metabolic characteristics that influence their recognition by immune cells resulting in a species-specific response. Although Saccharomyces boulardii is a widely studied probiotic yeast, immunostimulation by non-Saccharomyces yeasts still underexplored. Therefore, the aim of this study was to characterize the response induced in macrophages stimulated by yeasts Pichia kluyveri, Hanseniaspora uvarum, Candida intermedia and their derivatives: heat-killed cells, supernatant and DNA. RAW 264.7 murine macrophages were stimulated in vitro for 24 h and the response generated was evaluated by analyzing mRNA transcription of cytokines (IL2, IL4, IL10, IL13, IL23, TNF-α), transcription factors (Bcl6, NFκβ, STAT3), Toll-like receptor 2 (TLR2) and YM1 protein. Viable and heat-killed cells of P. kluyveri and H. uvarum were responsible for high levels of relative mRNA transcription of transcription factors and TLR2 (between 2 – 8-fold increase), however were able to induce only low transcription levels for analyzed cytokines (≤ 2-fold increase). Viable cells of C. intermedia were able to stimulate a significant transcription of IL4 (7.6-fold increase) and Bcl6 (4-fold increase), while heat-killed cells stimulated the highest level of TNF-α (2.4-fold increase) among yeasts and their derivatives. Furthermore, supernatant from C. intermedia culture induced significant (p < 0.05) levels of TLR2 (4.4-fold increase), being the only one among supernatants to present high levels of relative mRNA transcription of TLR2. Data found in this work arouse interest in further studies on interaction between non-Saccharomyces yeasts and immune system cells, mainly referring to immunomodulatory capacity.
An Information-Theoretic Scheme for Multi-Party Private Set Intersection

We investigate the problem of multi-party private set intersection (MP-PSI). In MP-PSI, there are $M$ parties, each storing a data set $\mathcal{P}_{i}$ over $N_{i}$ replicated and non-colluding databases, and we want to calculate the intersection of the data sets $\cap_{i=1}^{M}\mathcal{P}_{i}$ without leaking any information beyond the set intersection to any of the parties. For a specific communication protocol, we propose an information-theoretic scheme for MP-PSI based on the connection between the PSI problem and the multi-message symmetric private information retrieval (MM-SPIR) problem. Our scheme is a non-trivial generalization of the 2-party PSI scheme as it needs an intricate design of the shared common randomness. Interestingly, our scheme does not incur any penalty due to the more stringent privacy constraints in the MP-PSI problem compared to the 2-party PSI problem.
Intraspecific variation in longevity of Drosophila prolongata (Diptera: Drosophilidae) under solitary and group conditions

Considerable variations in behavior and physiology exist among sexes and strains of species. The amount and allocation of energy resources can affect the health and survival of individuals. If an individual devotes a large amount of energy to interact with other conspecifics, the resources may become too scarce to maintain their physical condition, which could reduce longevity. In this study, I examined the interactive effects of sex, strain, and the presence of conspecifics on adult longevity using four strains of Drosophila prolongata. This species shows a large intraspecific variation in behavior and morphology among isofemale strains. Under solitary conditions, longevity was significantly different among strains for both sexes. The effects of same‐sex conspecifics on adult longevity were also highly variable between the sexes and among strains. When exposed to conspecifics, the longevity of males of a hyper‐aggressive strain was more notably decreased than that of females of the same strain or either sex of other less aggressive strains. These results indicate that differences in the balance of costs and benefits of social interactions lead to differences in adult longevity under group conditions between the sexes and among strains within the same species.
Load-dependent Friction Laws of Three Models of Harmonic Drive Gearboxes Identified by Using a Force Transfer Diagram

Industrial robotics and aerospace engineering widely use harmonic drive gearboxes for their reliability, high accuracy with zero backlash and high ratio torque transmission However, they present known problematic behaviors that affect their performance. The article deals with the first step towards the improvement of torque control of collaborative robots. We designed and developed two experimental setups to study three types of Harmonic Drive gearboxes. We identify the friction laws by using Force Transfer Diagrams. The results exhibit a new parabolic law of friction torque as a function of the transmitted torque.
Slag Removal Path Estimation by Slag Distribution Image and Multi-Task Deep Learning Network

This paper proposes an automatic slag removal path estimation in a ladle image using a deep neural network. Slag removal is a hazardous task in steel production, and it is conducted manually by experienced human operators. To automate the slag removal task using a robotic machine, a slag removal path in a ladle image must be determined to control the motion of the machine. We propose a novel image structure called Slag Distribution Image(SDI) and a Slag Removal Path Estimation Network(SRPENet) to estimate the slag removal path. SDI contains the slag distribution and the ladle boundary information. SRPENet is designed as a multi-task learning architecture to perform two tasks: the first task is to estimate the control point of the slag removal path and the second task is to estimate the goodness-score of the control points. The structure of SDI is designed to yield efficient performance in SRPENet. The ground truth and learning data of slag removal path are collected along the working trajectories of human experts. The final removal path is determined by post-processing of the outputs of SRPENet. In experiments using real ladle images, the amount of removed slag and the mechanical energy efficiency are evaluated and compared with the ground truth to present qualitative and quantitative analysis. In addition, two ablation studies are presented. The first study is using SDI or RGB image as the input of SRPENet. The second study is the presence or absence of the smooth term in the SRPENet’s loss function. The proposed method shows 119.83% and 96.2% performance compared to ground truth in the amount of removed slag and mechanical energy efficiency, respectively. Our method runs in real-time with about 53.168 msec/frame.
Was Henry VIII Infertile? Miscarriages and Male Infertility in Tudor England

Abstract Although fertility has traditionally been viewed as the responsibility of women, recent studies suggest that reduced sperm function is a major cause of the recurrent pregnancy loss that affects 1 to 2 percent of couples. The reproductive and nutritional history of King Henry VIII indicates that 70 percent of the legitimate pregnancies attributed to Henry and his six wives resulted in miscarriage or stillbirth. By comparison, only 10 percent of the recorded pregnancies of the thirty-one noblemen closely associated with Henry had the same outcomes. Henry’s reproductive health likely contributed to the fertility problems for which his wives took the blame. The disregard of male infertility in Henry’s case may offer a clue to the reasons for the under-reporting of male reproductive health, then and now, to the detriment of both men and women.
Capacity and Construction of Recoverable Systems

Motivated by the established notion of storage codes, we consider sets of infinite sequences over a finite alphabet such that every $k$-tuple of consecutive entries is uniquely recoverable from its $l$-neighborhood in the sequence. In the first part of the paper we address the problem of finding the maximum growth rate of the set as well as constructions of explicit families (based on constrained coding) that approach the optimal rate. In the second part we consider a modification of the problem wherein the entries in the sequence are viewed as random variables over a finite alphabet, and the recovery condition requires that the Shannon entropy of the $k$-tuple conditioned on its $l$-neighborhood be bounded above by some $\epsilon > 0$. We study properties of measures on infinite sequences that maximize the metric entropy under the recoverability condition. Drawing on tools from ergodic theory, we prove some properties of entropy-maximizing measures. We also suggest a procedure of constructing an $\epsilon$-recoverable measure from a corresponding deterministic system, and prove that for small $\epsilon$ the constructed measure is a maximizer of the metric entropy.
Adaptive Underactuated Finger With Active Rolling Surface

This letter presents the design, prototype and kinematic model of a new adaptive underactuated finger with an articulated skin/surface that is able to bend and, at the same time, provides active rolling motion along its central axis while keeping the finger configuration (see Fig. 1). The design is based on a planar chain of overlapping spherical phalanxes that are tendon-driven. The finger has an articulated surface made of an external chain of hollow universal joints that can rotate via its central axis on the surface of the internal structure. The outer surface provides a second active Degree of Freedom (DoF). The two actuators, driving the bending and/or rolling motion, can be used independently. A set of experiments have been included to validate and measure the performance of the prototype for the grasping and rolling actions. The proposed finger can be built with a different number of phalanxes and sizes. A number of these fingers can be arranged along a palm structure resulting in a multi-finger robotic grasper for applications that require adaptation and in-hand manipulation capabilities such as pHRI.
A TDMA-Based Data Gathering Protocol for Molecular Communication via Diffusion-Based Nano-Sensor Networks

This paper explores the application of molecular communication via diffusion-based nano-sensor networks (MCSNs) for data gathering applications in in-body medical systems. For MCSNs, the large and varying propagation delay in the channel presents a fundamental challenge for channel access, leading to packet collisions. Although packet collisions are well-studied for traditional wireless sensor networks, to date, there are no such studies conducted for MCSNs. Another fundamental challenge is the limited capabilities of the nano-sensors, rendering the existing solutions inefficient. Therefore, a novel light-weight time-division multiple access (TDMA)-based data gathering multiple access control (MAC) protocol is proposed. Light-weight here implies that long information, such as timestamps, is not exchanged. TDMA-based here implies that each nano-sensor is designated an exclusive time-slot. The lack of a channel model for spherical transmitters impairs theoretical analysis of the probability of packet collisions. To overcome this, the propagation delay is approximated as a Normal distribution. The model is validated using the widely popular particle-based simulation, which is also used to determine the packet duration considering ON-OFF shift keying. Building upon these analyses, a system-level simulator is developed to evaluate the proposed MAC protocol. For the first time, the packet collision probability is characterized under varied distances and diffusion coefficients. A key finding is the correlation between the channel utilization and the time-slot occupancy ratio, which can be used as a tool to optimize the performance of an MCSN. Finally, comparisons with conventional TDMA reveals that the proposed protocol can offer better performance.
Socially-Aware Multi-Agent Following with 2D Laser Scans via Deep Reinforcement Learning and Potential Field

Target following in dynamic pedestrian environments is an important task for mobile robots. However, it is challenging to keep tracking the target while avoiding collisions in crowded environments, especially with only one robot. In this paper, we propose a multi-agent method for an arbitrary number of robots to follow the target in a socially-aware manner using only 2D laser scans. The multi-agent following problem is tackled by utilizing the complementary strengths of both reinforcement learning and potential field, in which the reinforcement learning part handles local interactions while navigating to the goals assigned by the potential field. Specifically, with the help of laser scans in obstacle map representation, the learning-based policy can help the robots avoid collisions with both static obstacles and dynamic obstacles like pedestrians in advance, namely socially aware. While the formation control and goal assignment for each robot is obtained from a target-centered potential field constructed using aggregated state information from all the following robots. Experiments are conducted in multiple settings, including random obstacle distributions and different numbers of robots. Results show that our method works successfully in unseen dynamic environments. The robots can follow the target in a socially compliant manner with only 2D laser scans.
A Community Based Randomized Controlled Trial to See the Effect of Vitamin D Supplementation on Development of Diabetes Among Women with Prediabetes Residing in A Rural Community of Northern India

Background: The primary objective of this study was to intervene with vitamin D supplementation in rural-based women with pre-diabetes (impaired fasting glucose or impaired glucose tolerance) to prevent development of type 2 diabetes (T2DM). Methods: This was an open-label randomized placebo-controlled trial conducted in rural women with pre-diabetes and vitamin D deficiency (Clinicaltrials.gov NCT02513888). Women aged 20-60 years with pre-diabetes were selected from rural Haryana (north India) and followed up for two years. A semi-structured questionnaire was used to collect information on socio-demographic and behavioral details, like sun exposure, dietary habits, etc., The intervention group received vitamin D supplementation while control group received lactose granules as placebo. Equal doses of calcium carbonate were given to both the groups. Results: A total of 132 participants were recruited in the study (58 each in the intervention and control groups). It was observed that there was no statistical significance in the incidence of diabetes in the control group as compared to the intervention group at the end of 2 years (P = 0.701). Conclusion: Though during the first year there was some delay in development of DM in the intervention group but at the end of two years there was no significant effect of vitamin D supplementation in delaying the incidence of diabetes in these women after two years. Trial registration: (Clinicaltrials.gov NCT02513888).
The Brown–Black Continuum of Light-Absorbing Combustion Aerosols

Brown carbon (BrC) exhibits highly variable light-absorption properties, with the imaginary part of the refractive indices (k) varying over several orders of magnitude. This poorly understood variability poses a challenge to accurately determining the BrC climate effect. Here, we present a framework to explain the variability in BrC k. We hypothesize that a fraction of BrC is composed of black-carbon (BC) precursors whose transformation to BC is not complete, and that there is a continuum of light-absorption properties along which BC and BrC lie. To test this hypothesis, we performed controlled-combustion experiments using benzene and toluene. By systematically varying the combustion conditions, we isolated BrC components along the brown–black continuum progressing from light (k = 0.004 at 550 nm) to dark (k = 0.25 at 550 nm). Using laser-desorption-ionization mass spectrometry and thermodenuder measurements, we show that the BrC progression from light to dark is associated with an increase in molecular s.
Microglia regulation of synaptic plasticity and learning and memory

Microglia are the resident macrophages of the central nervous system. Microglia possess varied morphologies and functions. Under normal physiological conditions, microglia mainly exist in a resting state and constantly monitor their microenvironment and survey neuronal and synaptic activity. Through the C1q, C3 and CR3 “Eat Me” and CD47 and SIRPα “Don’t Eat Me” complement pathways, as well as other pathways such as CX3CR1 signaling, resting microglia regulate synaptic pruning, a process crucial for the promotion of synapse formation and the regulation of neuronal activity and synaptic plasticity. By mediating synaptic pruning, resting microglia play an important role in the regulation of experience-dependent plasticity in the barrel cortex and visual cortex after whisker removal or monocular deprivation, and also in the regulation of learning and memory, including the modulation of memory strength, forgetfulness, and memory quality. As a response to brain injury, infection or neuroinflammation, microglia become activated and increase in number. Activated microglia change to an amoeboid shape, migrate to sites of inflammation and secrete proteins such as cytokines, chemokines and reactive oxygen species. These molecules released by microglia can lead to synaptic plasticity and learning and memory deficits associated with aging, Alzheimer’s disease, traumatic brain injury, HIV-associated neurocognitive disorder, and other neurological or mental disorders such as autism, depression and post-traumatic stress disorder. With a focus mainly on recently published literature, here we reviewed the studies investigating the role of resting microglia in synaptic plasticity and learning and memory, as well as how activated microglia modulate disease-related plasticity and learning and memory deficits. By summarizing the function of microglia in these processes, we aim to provide an overview of microglia regulation of synaptic plasticity and learning and memory, and to discuss the possibility of microglia manipulation as a therapeutic to ameliorate cognitive deficits associated with aging, Alzheimer’s disease, traumatic brain injury, HIV-associated neurocognitive disorder, and mental disorders.
CircLphn3 protects the blood-brain barrier in traumatic brain injury

Circular RNAs (circRNAs) are a new and large group of non-coding RNA molecules that are abundantly expressed in the central nervous system. However, very little is known about their roles in traumatic brain injury. In this study, we firstly screened differentially expressed circRNAs in normal and injured brain tissues of mice after traumatic brain injury. We found that the expression of circLphn3 was substantially decreased in mouse models of traumatic brain injury and in hemin-treated bEnd.3 (mouse brain cell line) cells. After overexpressing circLphn3 in bEnd.3 cells, the expression of the tight junction proteins, ZO-1, ZO-2, and occludin, was upregulated, and the expression of miR-185-5p was decreased. In bEnd.3 cells transfected with miR-185-5p mimics, the expression of ZO-1 was decreased. Dual-luciferase reporter assays showed that circLphn3 bound to miR-185-5p, and that miR-185-5p bound to ZO-1. Additionally, circLphn3 overexpression attenuated the hemin-induced high permeability of the in vitro bEnd.3 cell model of the blood-brain barrier, while miR-185-5p transfection increased the permeability. These findings suggest that circLphn3, as a molecular sponge of miR-185-5p, regulates tight junction proteins’ expression after traumatic brain injury, and it thereby improves the permeability of the blood-brain barrier. This study was approved by the Animal Care and Use Committee of Chongqing Medical University of China (approval No. 2021-177) on March 22, 2021.
Social skills and psychopathology are associated with autonomic function in children: a cross-sectional observational study

In recent years, the increase of psychopathological disorders in the population has become a health emergency, leading to a great effort to understand psychological vulnerability mechanisms. In this scenario, the role of the autonomic nervous system (ANS) has become increasingly important. This study investigated the association between ANS, social skills, and psychopathological functioning in children. As an ANS status proxy, we measured heart rate variability (HRV). Infants admitted to the neonatal intensive care unit of the University Hospital of Padova because of preterm birth or neonatal hypoxic-ischemic encephalopathy were sequentially recruited from January 2011 to June 2013 and followed long-term up to school age in this cross-sectional observational study. We recorded 5 minutes of HRV immediately before measuring performance in social abilities tasks (affect recognition and theory of mind, NEPSY-II) in 50 children (mean age 7.4 ± 1.4 years) with and without risk factors for developing neuropsychiatric disorders due to pre-/perinatal insults without major sequelae. Children also completed extensive cognitive, neuropsychological, and psychosocial assessment. Parents were assessed with psychopathological interviews and a questionnaire (CBCL 6-18). Analysis in a robust Bayesian framework was used to unearth dependencies between HRV, social skills, and psychopathological functioning. Social task scores were associated with HRV components, with high frequency the most consistent. HRV bands were also associated with the psychopathological questionnaire. Only normalized HRV high frequency was able to distinguish impaired children in the affect recognition task. Our data suggest that ANS may be implicated in social cognition both in typical and atypical developmental conditions and that HRV has cross-disease sensitivity. We suggest that HRV parameters may reflect a neurobiological vulnerability to psychopathology. The study was approved by the Ethics Committee of the University Hospital of Padova (Comitato Etico per la Sperimentazione, Azienda Opedaliera di Padova, approval No. 1693P).
Incorporating Sustainability into Supplier Development Process

Abstract Nowadays companies are more and more often expected to take responsibility for social and environmental impacts of their activities. When doing business social responsible company takes into consideration a wide range of its stakeholder’s expectations but also spread the social and environmental responsibility idea within the supply chain. Suppliers are the key stakeholders which directly influence the producer in terms of costs and quality of the offered products. However suppliers who offer high quality materials or components at an attractive price but at the same time not paying attention to their social and environmental impacts may devastate the buyer sustainability performance. Therefore the companies are trying to support suppliers in assuring their social and environmental responsibility as with this approach both sides benefit. In the study the authors used the case study method to present the proposal of integrating sustainability issues into already functioning supplier development process of a manufacturing company.