Miracle-dz/UniFAR-FTUs huggingface dataset:
Putting the Pieces Together: Mental Construction of Semantically Congruent and Incongruent Scenes in Dementia

Scene construction refers to the process by which humans generate richly detailed and spatially cohesive scenes in the mind’s eye. The cognitive processes that underwrite this capacity remain unclear, particularly when the envisaged scene calls for the integration of various types of contextual information. Here, we explored social and non-social forms of scene construction in Alzheimer’s disease (AD; n = 11) and the behavioural variant of frontotemporal dementia (bvFTD; n = 15) relative to healthy older control participants (n = 16) using a novel adaptation of the scene construction task. Participants mentally constructed detailed scenes in response to scene–object cues that varied in terms of their sociality (social; non-social) and congruence (congruent; incongruent). A significant group × sociality × congruence interaction was found whereby performance on the incongruent social scene condition was significantly disrupted in both patient groups relative to controls. Moreover, bvFTD patients produced significantly less contextual detail in social relative to non-social incongruent scenes. Construction of social and non-social incongruent scenes in the patient groups combined was significantly associated with independent measures of semantic processing and visuospatial memory. Our findings demonstrate the influence of schema-incongruency on scene construction performance and reinforce the importance of episodic–semantic interactions during novel event construction.
A probabilistic nodal loading model and worst case solutions for electric power system voltage stability assessment

In this paper, a new nodal loading model for use in voltage stability assessment of electric power systems is proposed, and the formulation of worst cases based on this model, as well as related numerical methods, are described. In this nodal loading model, called the "hyper-cone" model, a set of future operating points in a load parameter space is modeled. That is, the "vertex" of the hyper-cone is taken to be the current operating point, and the "thickness" of the hyper-cone represents the uncertainty of future loading. The worst loading case is the point, among the set of transfer limit points on or within the hyper-cone, at which the total load is smallest. In other words, in terms of the uncertainty of future loading, the worst case corresponds to the most conservative transfer limit. Efficient numerical methods to compute this worst case are shown, and these methods are demonstrated on some sample power systems including IEEE 118-node system.
A new life : Conversion of vacant office buildings into housing

Purpose – The vacancy of office buildings leads to financial problems for the owners and social problems for the community, e.g. vandalism, dereliction and deterioration. A solution may be found through the conversion of vacant office buildings into housing. Vacancy‐threatened buildings are often part of the mediocre part of the building stock. Does conversion make sense in this case? What are the opportunities, threats and risks? What are the critical success factors? The purpose of this paper is to discuss financial, functional, structural, technical and aesthetic issues.Design/methodology/approach – Through previous research at the Delft University of Technology, tools are developed to decide the potential for the conversion of buildings. This paper discusses the risks and chances, and brakes and triggers of transformation projects, based on case studies. These case studies are performed through interviews with professionals involved in the transformation process and through analyses of architectural d.
Sources of acid insoluble ash as marker of corn digestibility in broilers

The objective was to evaluate three sources of acid insoluble ash (AIA) (celite, kaolin, and sand), as indicators, to determine the apparent metabolizable energy of corn on a natural matter (AME) basis, dry matter digestibility coefficient (DMDC), and crude protein digestibility coefficient (CPDC) using total and partial excreta collection methods. Two hundred and ten Ross broiler chicks of 18 to 27 days of age were used. Broilers were adapted to experimental the diet for four days, and excreta were collected for 5 days. A reference diet (RD) based on corn and soybean meal was prepared to meet the nutritional requirements of the birds. A test diet was prepared with 40% replacement of RD with corn. The formulated diets were: D1, 99% Reference diet + 1% celite; D2, 59.4% RD + 39.6 % corn + 1% celite; D3, 99% Reference diet + 1% kaolin; D4, 59.4% RD + 39.6 % corn + 1% kaolin; D5, 99% Reference diet + 1% sand; D6, 59.4% RD + 39.6 % corn + 1% sand. The treatments were distributed in a completely randomized design, with six diets and five replicates of seven birds each in a 2x3 factorial arrangement. There were significant interactions for all variables investigated. It was observed that the AME and DMDC values of corn were similar in the two methods of collection, and PDC values using kaolin and celite makers were similar. However, the AME and CPDC of corn using sand with partial collection method were underestimated by 17.70 and 15.53%, respectively compared to those with the total collection method. The AME values of corn with the collection methods using celite and, the DMDC using celite and sand were significantly different. It was observed that the DMDC using celite and sand provided significantly lower values (4.67 and 5.15%), respectively, and the AME using celite was 2.86% lower than that obtained by total collection. To determine the EMA, DMDC, and CPDC in broilers, it is more efficient to use celiteTM and kaolin as markers with partial collection of excreta. Sand should not be used with partial excreta collection method, because it provides lower values of AME and CPDC compared to with total excreta collection method.
Effects of Adding Dietary Fiber on the Gut Microbiota, Short-Chain Fatty Acids and Metabolism of Layer Chickens

Dietary fiber is important for the growth performance and health of chickens. However, chickens must rely on fiber-degrading bacteria to grade fiber into monosaccharides due to a lack of endogenous fiber-degrading enzymes. Some of monosaccharides are then fermented into short-chain fatty acids (SCFAs) by SCFA-producing bacteria. SCFAs further regulate the host metabolism via special G protein-coupled receptors (GPRs) such as GPR43. In recent years, more and more research has focused on the impacts of adding dietary fiber on gut microorganisms and microbial metabolites-SCFAs of chickens. However, few works have focused on SCFA receptors and their impacts on metabolism of chickens. Understanding of this would help to explore how the dietary fiber affects chickens’ metabolism via SCFAs and their receptors. Given this, three different levels (0%, 1%, and 2%) of dietary fiber–eubiotic lignocellulose were added to the feed of ISA brown hens (IBH) for 0–8 weeks, with the aim of observing the effects of adding it on the gut microbiota, SCFAs, their receptors and metabolism of chickens. The results showed that the addition of 1% significantly increased the relative abundance of SCFAs-producing bacteria Sutterella, Oscillospira and Lactobacillus panis and the production of SCFAs (P < 0.05). The primer sequences of the GPR43 and reaction conditions designed in this experiment were applied to chickens. However, because the difference of the concentration of SCFAs was not great among groups, there was no significant change in the relative expression of the GPR43 mRNA in the liver and cecum (P > 0.05), resulting in there being no significant difference among groups in the appetite metabolism indexes including glucagon-like peptide-1 (GLP-1) and peptide tyrosine-tyrosine (PYY) and glucose metabolism indexes including blood glucose and liver glycogen of chickens (P > 0.05). The addition of 1% eubiotic lignocellulose is beneficial to increase the relative abundance of some SCFA-producing bacteria and the production of SCFAs at 8 weeks. The effects of added eubiotic lignocellulose on the relative expression of GPR43 mRNA and the metabolism of chickens were slight.
Economic Feasibility of Pipeline and Underground Reservoir Storage Options for Power-to-Gas Load Balancing

This paper investigates the economic feasibility of power-to-gas (P2G) systems and gas storage options for both H2 and renewable methane. The study is based on a techno-economic model in which the net present value (NPV) method and Monte Carlo simulation of risks and price forward curves for the electricity and the gas market are used. We study three investment cases: a Base Case where the gas is directly sold in the market, a Storage & Arbitrage Case where temporal arbitrage opportunities between the electricity and the gas market are exploited, and a Storage & Balancing Case where the balancing markets (secondary reserve market for electricity, external balancing market for natural gas) are addressed. The optimal type and size of different centralized and decentralized storage facilities are determined and compared with each other. In a detailed sensitivity and cost analysis, we identify the key factors which could potentially improve the economic viability of the technological concepts assessed. We find that the P2G system used for bridging the balancing markets for power and gas cannot be operated profitably. For both, temporal arbitrage and balancing energy, pipe storage is preferred. Relatively high feed-in tariffs (100 € MW-1 for hydrogen, 130 € MW-1 for methane) are required to render pipe storage for P2G economically viable.
Economic Feasibility of V2G Frequency Regulation in Consideration of Battery Wear

An economic feasibility study of vehicle-to-grid (V2G) frequency regulation is performed in consideration of battery wear. Usually, a transaction for frequency regulation is made in terms of power capacity while the battery-wear proceeds in proportion to the absolute amount of energy transferred. In order to relate the two quantities, we first estimate the amount of transferred energy in terms of contracted power capacity, and hence regulation income, by analyzing actual regulation signals and transactions. On the other hand, the amount of transferrable energy during the life cycle of a battery is estimated analyzing some pervasive specifications for electric vehicle (EV) batteries. The expected V2G income is then estimated and compared with battery prices to judge the economic feasibility of V2G regulation. In the latter part of the paper, the assessment result is validated with actual cycle life data of an EV battery cell. As a result, it is concluded that the estimated profit exceeds current market price of EV batteries, indicating that V2G regulation is an economically feasible service.
Modelling and control of a robotic arm actuated by nonlinear artificial muscles

Modern industrial robots are designed according to the principal design rules to construct light and stiff. These design rules are not suitable for robots to be used in a domestic environment. Industrial robots are stiff and strong and, for these reasons, dangerous to humans. To allow for robots to be safe in a domestic environment, they need to be compliant. So, in case a domestic robot comes in contact with a human, this does not lead to injuries. Several options are available to make robots compliant. One option is to use compliant actuators, for example a McKibben muscle. This is a pneumatic artificial muscle with great resemblance to a biological muscle. A McKibben muscle consists of a 15 cm piece of bicycle tube, surrounded by a nylon braid of 20 cm. The endings of the tube and the braid are connected using a fitting. Inflating the muscle yields a decrease in muscle length and an increase in diameter and stiffness. To perform research on the applicability of McKibben muscles as robotic actuators, a robotic arm is constructed at Philips Applied Technologies in Eindhoven. It has two degrees of freedom and is actuated by four McKibben muscles. The research goals are, firstly, to construct a predictive model of the robotic arm including McKibben muscles and, secondly, to construct controllers that guarantee accuratemotion control of the robotic arm, using model knowledge on the robotic arm and the muscles. A predictive model of the McKibbenmuscle is proposed, which takes into account the change in muscle shape as well as in stiffness. This model is used in the total robotic arm model, also including the pneumatics and the rigid body dynamics of the arm. Dedicated experiments are performed to identify the parameters of the muscle model and the robotic arm model. Other experiments are used to validate whether the models give a correct prediction of the experimental robotic arm behavior. It appears that the robotic arm behavior is predicted correctly within a limited pressure range. The main model error is in the description of the muscle stiffness. The knowledge gained by the experiments and the modelling is used to define a control strategy. By driving the muscles in pairs, the robotic arm is stabilized completely using linear feedback controllers. Each muscle pair requires two controllers: one to control the robotic arm position and one to control the pressure in both muscles. The stiffness variation as a function of the muscle length of the McKibben muscles is completely compensated for by applying a notch-filter in the position controller. The controllers are implemented on both a oneand two-degree-of-freedom variant of the experimental system. Closed-loop experiments show the effectiveness of the control strategy, where the feasible bandwidth of this controlled system is 4 Hz. To improve the predictive capacities of the robotic arm model, future research on the force balance inside a muscle and the subsequent stiffness is required and advised.
Dissecting the Complexity of Early Heart Progenitor Cells

Early heart development depends on the coordinated participation of heterogeneous cell sources. As pioneer work from Adriana C. Gittenberger-de Groot demonstrated, characterizing these distinct cell sources helps us to understand congenital heart defects. Despite decades of research on the segregation of lineages that form the primitive heart tube, we are far from understanding its full complexity. Currently, single-cell approaches are providing an unprecedented level of detail on cellular heterogeneity, offering new opportunities to decipher its functional role. In this review, we will focus on three key aspects of early heart morphogenesis: First, the segregation of myocardial and endocardial lineages, which yields an early lineage diversification in cardiac development; second, the signaling cues driving differentiation in these progenitor cells; and third, the transcriptional heterogeneity of cardiomyocyte progenitors of the primitive heart tube. Finally, we discuss how single-cell transcriptomics and epigenomics, together with live imaging and functional analyses, will likely transform the way we delve into the complexity of cardiac development and its links with congenital defects.
The Relative Performance of Filled and Feedhorn-Coupled

Modern far infrared and submillimeter instruments require large format arrays. We consider the relative performance of filled array (bare pixel) and feedhorn-coupled architectures for bolometer focal planes. Based on typical array parameters, we quantify the relative observing speeds and comment on the merits of the different architectures. Filled arrays can provide higher mapping speed (by a factor of up to 3.5) and simpler observing modes at the expense of reduced sensitivity for pointed observations, increased detector numbers, and greater vulnerability to stray light and electromagnetic interference. Taking advantage of the filled array architecture requires strongly background limited detectors. At millimeter wavelengths, filled arrays must be surrounded by a sufficiently cold enclosure to minimize the background power from the instrument itself.
Long‐term degradation from marshes into meadows shifts microbial functional diversity of soil phosphorus cycling in an alpine wetland of the Tibetan Plateau

Soil microbes greatly contribute to the regulating of phosphorus (P) cycling, which plays a significant role in maintaining wetland ecosystem processes and function. The microbial functional diversity of soil P cycling in response to wetland degradation, however, remains largely unknown. We used metagenomic sequencing to investigate the microbial community and genes related to soil P cycling in un‐degraded marshes and meadows derived from long‐term marsh degradation in the Lalu alpine wetland of the Tibetan Plateau. When the marsh degraded into meadow, organic P (OP) mineralization genes increased while genes related to P‐starvation response regulation decreased. Proteobacteria (20.5–74.3%) and Actinobacteria (5.6–59.7%) were the dominant phyla in soils and were also the main contributors (39.7–84.1% in total) to soil P‐cycling genes. Soil pH was the primary factor influencing the P‐cycling functional genes. Soil pH negatively affected the genes related to the P‐uptake and transport system and had negative effects on the genes related to P‐starvation response regulation, OP mineralization, and inorganic P solubilization. These findings may deepen our understanding of the biogeochemical process of soil OP and may be beneficial for wetland management.
Sensor Fusion for Effective Hand Motion Detection

OF THE DISSERTATION SENSOR FUSION FOR EFFECTIVE HAND MOTION DETECTION by Fatemeh Abyarjoo Florida International University, 2015 Miami, Florida Professor Armando Barreto, Major Professor Human hands have a critical role in many human activities. There are many applications in the field of human computer interaction where it is necessary to monitor human hand motions. Different technologies have been employed to track the human hand motion. However, many of those approaches did not work well in real life situations. This research focused on tracking the human hand motion so that it can be used regardless of location or environmental lightening. MEMS (MicroElectro-Mechanical sensors) inertial and magnetic sensors were used in this study for tracking the palm and the thumb motions. In this dissertation a sensor fusion algorithm was proposed to track the threedimensional rotational motion of the human hand. The proposed sensor fusion algorithm was a quaternion-based Kalman filter. Two optimization methods (Gradient Descent and Newton-Gauss) were utilized to estimate the corresponding quaternion vector using the observation vector in the Kalman filtering process. Two sensor units were attached on a glove on the palm and thumb sections to record the motion related data. As the articulation of the remaining four fingers (index, middle, ring and pinky) to the palm are more restricted than the thumb, the applied approach for the thumb can be applicable for other fingers. It is challenging to compute the rotational motion using MESMS sensors with acceptable accuracy because the MEMS sensors are prone to different types of sys-
Validity of the Wrist-Worn Polar Vantage V2 to Measure Heart Rate and Heart Rate Variability at Rest

Heart rate (HR) and heart rate variability (HRV) can be monitored with wearable devices throughout the day. Resting HRV in particular, reflecting cardiac parasympathetic activity, has been proposed to be a useful marker in the monitoring of health and recovery from training. This study examined the validity of the wrist-based photoplethysmography (PPG) method to measure HR and HRV at rest. Recreationally endurance-trained participants recorded pulse-to-pulse (PP) and RR intervals simultaneously with a PPG-based watch and reference heart rate sensor (HRS) at a laboratory in a supine position (n = 39; 5-min recording) and at home during sleep (n = 29; 4-h recording). In addition, analyses were performed from pooled laboratory data (n = 11344 PP and RR intervals). Differences and correlations were analyzed between the HRS- and PPG-derived HR and LnRMSSD (the natural logarithm of the root mean square of successive differences). A very good agreement was found between pooled PP and RR intervals with a mean bias of 0.17 ms and a correlation coefficient of 0.993 (p < 0.001). In the laboratory, HR did not differ between the devices (mean bias 0.0 bpm), but PPG slightly underestimated the nocturnal recordings (mean bias −0.7 bpm, p < 0.001). PPG overestimated LnRMSSD both in the laboratory (mean bias 0.20 ms, p < 0.001) and nocturnal recordings (mean bias 0.17 ms, p < 0.001). However, very strong intraclass correlations in the nocturnal recordings were found between the devices (HR: 0.998, p < 0.001; LnRMSSD: 0.931, p < 0.001). In conclusion, PPG was able to measure HR and HRV with adequate accuracy in recreational athletes. However, when strict absolute values are of importance, systematic overestimation, which seemed to especially concern participants with low LnRMSSD, should be acknowledged.
A Study of Mobility Management Support for AR/VR-based Cognition Recovery and Rehabilitation

Cognition recovery and rehabilitation programs are essential to improve the well-being of the elderly and person's suffering from cognitive impairments and chronic diseases. Most of this programs have utilized augmented reality/virtual reality (AR/VR) technologies to enable an immersive cognitive training through virtual environments capable of providing a realistic cognitive task simulations. This paper deals with leveraging the features of AR/VR technologies to improve the performance of cognition recovery and rehabilitation programs specifically on the seamless transmission of physiological information over open network systems. It aims to include mobility management as an integral factor in measuring the quality of service (QoS) for such feature of the healthcare system. In this regard, it is proposed to utilize the network-based Proxy Mobile Internet Protocol version 6 (PMIPv6) mobility management protocol to fully implement a seamless mobility support for the system, thus, making the elderly and those with cognitive impairments become more productive and active members of the society. Keyword : Healthcare systems, AR/VR, Cognition recovery and rehabilitation, PMIPv6, Mobility management
Nonwearable Sensor-Based In-Home Assessment of Subtle Daily Behavioral Changes as a Candidate Biomarker for Mild Cognitive Impairment

Patients show subtle changes in daily behavioral patterns, revealed by traditional assessments (e.g., performance- or questionnaire-based assessments) even in the early stage of Alzheimer’s disease (AD; i.e., the mild cognitive impairment (MCI) stage). An increase in studies on the assessment of daily behavioral changes in patients with MCI and AD using digital technologies (e.g., wearable and nonwearable sensor-based assessment) has been noted in recent years. In addition, more objective, quantitative, and realistic evidence of altered daily behavioral patterns in patients with MCI and AD has been provided by digital technologies rather than traditional assessments. Therefore, this study hypothesized that the assessment of daily behavioral changes with digital technologies can replace or assist traditional assessment methods for early MCI and AD detection. In this review, we focused on research using nonwearable sensor-based in-home assessment. Previous studies on the assessment of behavioral changes in MCI and AD using traditional performance- or questionnaire-based assessments are first described. Next, an overview of previous studies on the assessment of behavioral changes in MCI and AD using nonwearable sensor-based in-home assessment is provided. Finally, the usefulness and problems of nonwearable sensor-based in-home assessment for early MCI and AD detection are discussed. In conclusion, this review stresses that subtle changes in daily behavioral patterns detected by nonwearable sensor-based in-home assessment can be early MCI and AD biomarkers.