Miracle-dz/UniFAR-FTUs huggingface dataset:
Cognitive and Affective Empathy in Eating Disorders: A Systematic Review and Meta-Analysis

Background: Recent models of eating disorders (EDs) have proposed social and emotional difficulties as key factors in the development and maintenance of the illness. While a number of studies have demonstrated difficulties in theory of mind and emotion recognition, little is known about empathic abilities in those with EDs. Further, few studies have examined the cognitive-affective empathy profile in EDs. The aim of this systematic review and meta-analysis was to provide a synthesis of empathy studies in EDs, and examine whether those with EDs differ from healthy controls (HC) on self-reported total, cognitive, and affective empathy. Methods: Electronic databases were systematically searched for studies using self-report measures of empathy in ED populations. In total, 17 studies were identified, 14 of which could be included in the total empathy meta-analysis. Eight of the 14 studies were included in the cognitive and affective empathy meta-analyses. Results: Meta-analyses showed that while total empathy and affective empathy scores did not differ between those with anorexia nervosa (AN) and HC, those with AN had significantly lower cognitive empathy scores compared to HCs (small effect size). Meta-analyses of Interpersonal Reactivity Index sub-scores revealed that AN had significantly lower Fantasy scores than HC (small effect size), indicating that those with AN have more difficulty in identifying themselves with fictional characters. Only 3 studies examined empathy in those with bulimia nervosa (BN) or binge eating disorder (BED). Conclusions: The lowered cognitive empathy and intact affective empathy profile found in AN is similar to that found in other psychiatric and neurodevelopmental conditions, such as autism spectrum disorder (ASD). These findings add to the literature characterizing the socio-emotional phenotype in EDs. Future research should examine the influence of comorbid psychopathology on empathy in EDs.
Stability Region of Droop-Controlled Distributed Generation in Autonomous Microgrids

This paper proposes a conceptual framework for geometrically characterizing the small-disturbance stable operating area of an autonomous microgrid. A concept of stability region of distributed generation (DGSR) is established on a general differential-algebraic-equation model of autonomous microgrids. It provides a graphical tool to characterize the limits for a microgrid to accommodate the distributed, volatile, and uncertain power generation of renewable energy, inside which the stability of the system can be guaranteed. The Kernel Ridge Regression method is employed to accurately and quickly estimate the boundary of the DGSR, leading to its approximate expression in an analytical form. The DGSR allows for a straightforward and intuitive evaluation of stability and provides guidance for adjustments to enhance it. Case studies on two autonomous microgrids are used to verify the performance of the proposed DGSR and its potential applications.
Discovering Individual Life Style From Anonymized WiFi Scan Lists on Smartphones

The prevalence of smartphones equipped with various sensors enables the pervasive capture of users’ location data. WiFi scan lists on one smartphone, i.e., scan results of the network in a range, can roughly indicate the physical location of the phone in a time period. Considering the close relationship between location and daily life, users’ lifestyle can be inferred from their WiFi scan lists. Given the issue of user privacy, in this paper, we explore anonymized WiFi scan lists to discover users’ lifestyle. Individual lifestyle about mobility and important places of home and workplaces is discovered, respectively, based on the stay places extracted from anonymized WiFi scan lists and the reconstructed mobility trajectories. We first learn the lifestyle about mobility by detecting activity areas from mobility trajectories and introducing two metrics of activeness and diversity to measure individual mobility. Then, we discover the lifestyle about the home and workplaces identified from anonymized WiFi scan lists, such as stay duration at home, activeness of going outside at night, and working hours on weekdays and weekends. The experiments were conducted on a real-world large-scale dataset, which contains records of smartphone usage of more than 17 000 volunteering participants. Our work is a promising step toward automatically discover people’s lifestyle from anonymized smartphone data.
A Time-Domain-Controlled Current-Mode Buck Converter With Wide Output Voltage Range

The controller of a current-mode buck converter is realized by only time-domain circuits such as voltage-controlled oscillator (VCO), voltage-controlled delay line (VCDL), and phase detector (PD). The inductor current is sensed by a VCO, which helps improving power efficiency and eliminates the need for the slope compensation preventing the sub-harmonic oscillation. The type-II frequency compensation network is realized by a combination of VCO and VCDL without an error amplifier (EA) and RC network which may consume large power and occupy large silicon area. Instead of voltage comparator, a PD detects the error of the output voltage, which allows the switching duty cycle and thus the output voltage to be controlled in a wide range. With the proposed time-domain current-mode controller, a buck converter has been implemented in a 65-nm CMOS process. The output voltage can be regulated from 0.15 to 1.69 V from a 1.8-V input and the maximum load current is 0.6 A. The peak power efficiency is 94.9% when the output is 1.5 V and the load current is 250 mA. The load transient speed is better than 3.5 <inline-formula> <tex-math notation="LaTeX">$\mu \text{s}$ </tex-math></inline-formula> for both the step-up and step-down changes of the load current by 480 mA in 0.1 <inline-formula> <tex-math notation="LaTeX">$\mu \text{s}$ </tex-math></inline-formula>.
Transcriptional Regulation of Stearoyl-Acyl Carrier Protein Desaturase Genes in Response to Abiotic Stresses Leads to Changes in the Unsaturated Fatty Acids Composition of Olive Mesocarp

In higher plants, the stearoyl-acyl carrier protein desaturase (SAD) catalyzes the first desaturation step leading to oleic acid, which can be further desaturated to linoleic and α-linolenic acids. Therefore, SAD plays an essential role in determining the overall content of unsaturated fatty acids (UFA). We have investigated how SAD genes expression and UFA composition are regulated in olive (Olea europaea) mesocarp tissue from Picual and Arbequina cultivars in response to different abiotic stresses. The results showed that olive SAD genes are transcriptionally regulated by temperature, darkness and wounding. The increase in SAD genes expression levels observed in Picual mesocarp exposed to low temperature brought about a modification in the UFA content of microsomal membrane lipids. In addition, darkness caused the down-regulation of SAD genes transcripts, together with a decrease in the UFA content of chloroplast lipids. The differential role of olive SAD genes in the wounding response was also demonstrated. These data point out that different environmental stresses can modify the UFA composition of olive mesocarp through the transcriptional regulation of SAD genes, affecting olive oil quality.
MMSE Receiver Design and SINR Calculation in MU-MIMO Systems With Imperfect CSI

The performance of the uplink of multiuser multiple input multiple output systems depends critically on the receiver architecture and on the quality of the acquired channel state information. A popular approach is to design linear receivers that minimize the mean squared error (MSE) of the received data symbols. Unfortunately, most of the literature does not take into account the presence of channel state information errors in the MSE minimization. In this letter we develop a linear minimum MSE (MMSE) receiver that employs the noisy instantaneous channel estimates to minimize the MSE, and highlight the dependence of the receiver performance on the pilot-to-data power ratio. By invoking the theory of random matrices, we calculate the users’ signal-to-interference-plus-noise ratio as a function of the number of antennas and the pilot-to-data power ratio of all users. Numerical results indicate that this new linear receiver outperforms the classical mismatched MMSE receiver.
Children's Cortisol and Cell-Free DNA Trajectories in Relation to Sedentary Behavior and Physical Activity in School: A Pilot Study

The worldwide prevalence of mental disorders in children and adolescents increased constantly. Additionally, the recommended amount of physical activity (PA) is not achieved by this age group. These circumstances are associated with negative impacts on their health status in later life and can lead to public health issues. The exposure to natural green environments (NGE) seems to be beneficial for human health. The compulsory school system offers great opportunities to reach every child with suitable health-related contents and interventions at an early stage. The concept of Education Outside the Classroom (EOtC) uses NGE and sets focus on PA. Therefore, EOtC might be a beneficial educational intervention to promote students health. The association between biological stress markers and sedentary behavior (SB) plus PA is insufficiently evaluated in school settings. This exploratory study aims to evaluate the association between students' cortisol, plus circulating cell-free deoxyribonucleic acid (cfDNA) levels, and their SB, light PA (LPA), and moderate-to-vigorous PA (MVPA). We assessed data from an EOtC program (intervention group [IG], n = 37; control group [CG], n = 11) in three seasons (fall/spring/summer) in outdoor lessons (IG) in a NGE and normal indoor lessons (CG). SB and PA were evaluated by accelerometry, and cortisol and cfDNA levels by saliva samples. Fitted Bayesian hierarchical linear models evaluated the association between cortisol and cfDNA, and compositional SB/LPA/MVPA. A steady decline of cortisol in the IG is associated with relatively high levels of LPA (posterior mean = −0.728; credible interval [CRI 95%]: −1.268; −0.190). SB and MVPA tended to exhibit a similar effect in the CG. A high amount of cfDNA is positively associated with a relatively high amount of SB in the IG (posterior mean, 1.285; CRI: 0.390; 2.191), the same association is likely for LPA and MVPA in both groups. To conclude, LPA seems to support a healthy cortisol decrease in children during outdoor lessons in NGEs. Associations between cfDNA and SB/PA need to be evaluated in further research. This study facilitates the formulation of straightforward and directed hypotheses for further research with a focus on the potential health promotion of EOtC.
Cache-Aided Interference Channels

Over the past decade, the bulk of wireless traffic has shifted from speech to content. This shift creates the opportunity to cache part of the content in memories closer to the end users, for example in base stations. Most previous paper focuses on the reduction of load in the backhaul and core networks due to caching, i.e., on the benefits caching offers for the wireline communication link between the origin servers and the caches. In this paper, we are instead interested in the benefits caching can offer for the wireless communication link between the caches and the end users. To quantify the gains of caching for this wireless link, we consider an interference channel in which each transmitter is equipped with an isolated cache memory. Communication takes place in two phases, a content placement phase followed by a content delivery phase. The objective is to design both the placement and the delivery phases to maximize the rate in the delivery phase in response to any possible user demands. Focusing on the three-user case, we show that through careful joint design of these phases, we can reap three distinct benefits from caching: a load balancing gain, an interference cancellation gain, and an interference alignment gain. In our proposed scheme, load balancing is achieved through a specific file splitting and placement, producing a particular pattern of content overlap at the caches. This overlap allows to implement interference cancellation. Furthermore, it allows us to create several virtual transmitters, each transmitting a part of the requested content, which increases interference-alignment possibilities.
Quantitative Comparison of Photoplethysmographic Waveform Characteristics: Effect of Measurement Site

Introduction: Photoplethysmography (PPG) has been widely used to assess cardiovascular function. However, few studies have comprehensively investigated the effect of measurement site on PPG waveform characteristics. This study aimed to provide a quantitative comparison on this. Methods: Thirty six healthy subjects participated in this study. For each subject, PPG signals were sequentially recorded for 1 min from six different body sites (finger, wrist under (anatomically volar), wrist upper (dorsal), arm, earlobe, and forehead) under both normal and deep breathing patterns. For each body site under a certain breathing pattern, the mean amplitude was firstly derived from recorded PPG waveform which was then normalized to derive several waveform characteristics including the pulse peak time (Tp), dicrotic notch time (Tn), and the reflection index (RI). The effects of breathing pattern and measurement site on the waveform characteristics were finally investigated by the analysis of variance (ANOVA) with post hoc multiple comparisons. Results: Under both breathing patterns, the PPG measurements from the finger achieved the highest percentage of analyzable waveforms for extracting waveform characteristics. There were significant effects of breathing pattern on Tn and RI (larger Tn and smaller RI with deep breathing on average, both p < 0.03). The effects of measurement site on mean amplitude, Tp, Tn, and RI were significant (all p < 0.001). The key results were that, under both breathing patterns, the mean amplitude from finger PPG was significantly larger and its Tp and RI were significantly smaller than those from the other five sites (all p < 0.001, except p = 0.04 for the Tp of “wrist under”), and Tn was only significantly larger than that from the earlobe (both p < 0.05). Conclusion: This study has quantitatively confirmed the effect of PPG measurement site on PPG waveform characteristics (including mean amplitude, Tp, Tn, and RI), providing scientific evidence for a better understanding of the PPG waveform variations between different body sites.
Exploring, Mapping, and Data Management Integration of Habitable Environments in Astrobiology

New approaches to blending geoscience, planetary science, microbiology-geobiology/ecology, geoinformatics and cyberinfrastructure technology disciplines in a holistic effort can be transformative to astrobiology explorations. Over the last two decades, overwhelming orbital evidence has confirmed the abundance of authigenic (in situ, formed in place) minerals on Mars. On Earth, environments where authigenic minerals form provide a substrate for the preservation of microbial life. Similarly, extraterrestrial life is likely to be preserved where crustal minerals can record and preserve the biochemical mechanisms (i.e., biosignatures). The search for astrobiological evidence on Mars has focused on identifying past or present habitable environments – places that could support some semblance of life. Thus, authigenic minerals represent a promising habitable environment where extraterrestrial life could be recorded and potentially preserved over geologic time scales. Astrobiology research necessarily takes place over vastly different scales; from molecules to viruses and microbes to those of satellites and solar system exploration, but the differing scales of analyses are rarely connected quantitatively. The mismatch between the scales of these observations— from the macro- satellite mineralogical observations to the micro- microbial observations— limits the applicability of our astrobiological understanding as we search for records of life beyond Earth. Each-scale observation requires knowledge of the geologic context and the environmental parameters important for assessing habitability. Exploration efforts to search for extraterrestrial life should attempt to quantify both the geospatial context and the temporal/spatial relationships between microbial abundance and diversity within authigenic minerals at multiple scales, while assimilating resolutions from satellite observations to field measurements to microscopic analyses. Statistical measures, computer vision, and the geospatial synergy of Geographic Information Systems (GIS), can allow analyses of objective data-driven methods to locate, map, and predict where the “sweet spots” of habitable environments occur at multiple scales. This approach of science information architecture or an “Astrobiology Information System” can provide the necessary maps to guide researchers to discoveries via testing, visualizing, documenting, and collaborating on significant data relationships that will advance explorations for evidence of life in our solar system and beyond.
National-scale Traffic Model Calibration in Real Time with Multi-source Incomplete Data

Real-time traffic modeling at national scale is essential to many applications, but its calibration is extremely challenging due to its large spatial and fine temporal coverage. The existing work is focused on urban-scale calibration with complete field data from single data sources (e.g., loop sensors or taxis), which cannot be generalized to national scale because complete single-source field data at national scale are almost impossible to obtain. To address this challenge, in this article, we design MultiCalib, a model calibration framework to optimize traffic models based on multiple incomplete data sources at national scale in real time. Instead of simply combining multi-source data, we theoretically formulate a multi-source model calibration problem based on real-world contexts and multi-view learning. In particular, we design (i) convex multi-view learning to integrate multi-source data by quantifying biases of data sources, and (ii) context-aware tensor decomposition to infer incomplete multi-source data by extracting real-world contexts. More importantly, we implement and evaluate MultiCalib with two heterogeneous nationwide vehicle networks with 340,000 vehicles to infer traffic conditions on 36 expressways and 119 highways, along with four cities across China. The results show that MultiCalib outperforms baseline calibration by 25% on average with the same input data. Based on the proposed national-scale traffic model calibration, we design a novel dispatching framework integrated with our speed calibration model where we guide a vehicular fleet among national-scale highways with a routing strategy to reduce general traveling time. The results show that a routing strategy based on MultiCalib outperforms a routing strategy based on a state-of-the-art traffic model by 45% on average.
Secure Outage Probability Analysis of Relay Networks Based on Cooperative Jamming

In view of the security of the relay system with eavesdropping node, the secure outage probability of relay system under cooperative jamming mechanism is studied based on the theory of physical layer security. The method of transmitting jamming signals by the source node and destination node is proposed to make the receiving of eavesdropping node worse than the legal node, improving the secure performance of the system. Meanwhile, the self-interference caused by the relay node in the full-duplex is avoided. The theoretical derivation of the system's secure outage probability is also made. The simulation results show that compared with the traditional relay network, the proposed system's secure outage probability is significantly reduced by using cooperative jamming technology. In addition, with the cooperative jamming mechanism, the secure outage probability of the proposed half-duplex network is better than that of full-duplex network.
Gut Hormones and Their Effect on Bone Metabolism. Potential Drug Therapies in Future Osteoporosis Treatment

Bone homeostasis displays a circadian rhythm with increased resorption during the night time as compared to day time, a difference that seems—at least partly—to be caused by food intake during the day. Thus, ingestion of a meal results in a decrease in bone resorption, but people suffering from short bowel syndrome lack this response. Gut hormones, released in response to a meal, contribute to this link between the gut and bone metabolism. The responsible hormones appear to include glucose-dependent insulinotropic polypeptide (GIP) and glucagon-like peptide-1 (GLP-1), known as incretin hormones due to their role in regulating glucose homeostasis by enhancing insulin release in response to food intake. They interact with their cognate receptors (GIPR and GLP-1R), which are both members of the class B G protein-coupled receptors (GPCRs), and already recognized as targets for treatment of metabolic diseases, such as type 2 diabetes mellitus (T2DM) and obesity. Glucagon-like peptide-2 (GLP-2), secreted concomitantly with GLP-1, acting via another class B receptor (GLP-2R), is also part of this gut-bone axis. Several studies, including human studies, have indicated that these three hormones inhibit bone resorption and, moreover, that GIP increases bone formation. Another hormone, peptide YY (PYY), is also secreted from the enteroendocrine L-cells (together with GLP-1 and GLP-2), and acts mainly via interaction with the class A GPCR NPY-R2. PYY is best known for its effect on appetite regulation, but recent studies have also shown an effect of PYY on bone metabolism. The aim of this review is to summarize the current knowledge of the actions of GIP, GLP-1, GLP-2, and PYY on bone metabolism, and to discuss future therapies targeting these receptors for the treatment of osteoporosis.
Searching for Bacteria in Neural Tissue From Amyotrophic Lateral Sclerosis

Despite great efforts in the investigation, the exact etiology of amyotrophic lateral sclerosis (ALS) is a matter of intensive research. We recently advanced the idea that ALS might be caused by fungal infection. Indeed, fungal yeast and hyphal structures can be directly visualized in neural tissue of ALS patients, and a number of fungal species have been identified in the central nervous system (CNS). In the present work, we tested the possibility that bacterial infections can accompany these mycoses. Our findings establish the presence of bacterial DNA in different regions of the CNS from all ALS patients examined. Specifically, we used PCR and next generation sequencing (NGS) to precisely determine the bacterial species present in ALS tissue. Consistent with these findings, immunohistochemistry analysis of CNS sections using specific anti-bacterial antibodies identified prokaryotic cells in neural tissue. Finally, we assayed for the repeat expansion of the hexanucleotide repeat GGGGCC in C9orf72, which is considered the most common genetic cause of ALS in patients, using DNA extracted from ALS CNS tissue. We failed to find this repeated sequence in any of the eleven patients analyzed. Our results indicate that bacterial DNA and prokaryotic cells are present in CNS tissue, leading to the concept that both fungal and bacterial infections coexist in patients with ALS. These observations lay the groundwork for the use of appropriate therapies to eradicate the polymicrobial infections in ALS.