Miracle-dz/UniFAR-FTUs huggingface dataset:
Recovery of CYP3A Phenotype after Kidney Transplantation

End-stage renal disease impairs drug metabolism via cytochrome P450 CYP3A; however, it is unclear whether CYP3A activity recovers after kidney transplantation. Therefore, the aim of this study was to evaluate the change in CYP3A activity measured as 4β-hydroxycholesterol (4βOHC) concentration after kidney transplantation. In total, data from 58 renal transplant recipients with 550 prospective 4βOHC measurements were included in the study. One sample per patient was collected before transplantation, and 2–12 samples per patient were collected 1–82 days after transplantation. The measured pretransplant 4βOHC concentrations ranged by >7-fold, with a median value of 22.8 ng/ml. Linear mixed-model analysis identified a 0.16-ng/ml increase in 4βOHC concentration per day after transplantation (P < 0.001), indicating a regain in CYP3A activity. Increasing estimated glomerular filtration rate after transplantation was associated with increasing 4βOHC concentration (P < 0.001), supporting that CYP3A activity increases with recovering uremia. In conclusion, this study indicates that CYP3A activity is regained subsequent to kidney transplantation.
Square topology: A novel topology for NoCs

This paper proposes square topology as an efficient topology for Network-on-Chips (NoCs). Although the proposed topology imposes the cost near to that of the mesh topology, the proposed topology 1) provides lower diameter for NoC, 2) offers better performance under uniform and hotspot traffic pattern. In our simulation, the proposed square topology had better performance in comparison to other topologies specifically meshes and spidergon topology.
An Introduction to Inertial and Visual Sensing

In this paper we present a tutorial introduction to two important senses for biological and robotic systems — inertial and visual perception. We discuss the fundamentals of these two sensing modalities from a biological and an engineering perspective. Digital camera chips and micro-machined accelerometers and gyroscopes are now commodities, and when combined with today's available computing can provide robust estimates of self-motion as well 3D scene structure, without external infrastructure. We discuss the complementarity of these sensors, describe some fundamental approaches to fusing their outputs and survey the field.
Mobile Application Platform Heterogeneity: Android vs Windows Phone vs iOS vs Firefox OS

Modern smartphones have a rich spectrum of increasingly sophisticated features, opening opportunities for software-led innovation. Of the large number of platforms to develop new software on, in this paper we look closely at three platforms identified as market leaders for the smartphone market by Gartner Group in 2013 and one platform, Firefox OS, representing a new paradigm for operating systems based on web technologies. We compare the platforms in several different categories, such as software architecture, application development, platform capabilities and constraints, and, finally, developer support. Using the implementation of a mobile version of the tic-tac-toe game on all the four platforms, we seek to investigate strengths, weaknesses and challenges of mobile application development on these platforms. Big differences are highlighted when inspecting community environments, hardware abilities and platform maturity. These inevitably impact upon developer choices when deciding on mobile platform development strategies.
Keystroke/mouse usage based emotion detection and user identification

Emotions are primarily thought of as mental experiences of body states, which are mostly shown in the face with precise and specific muscle patterns. It is, perhaps, the most critical attribute of living beings, and is extremely difficult to detect and generate artificially. Its detection always remains a well-explored classical problem. Existing approaches for detecting human emotions generally demand significant infrastructural overheads. Excluding these overheads, in this paper, we propose a much simpler way of emotion detection. To do so, We have induced different states of emotion through different multimedia components, and then collected participants' keystrokes (free text) and mouse usage data through a custom-developed survey. We have used several existing classifiers (KNN, KStar, RandomCommittee and RandomForest) and a newly proposed light-weight classifier namely Bounded K-means Clustering, to analyze those usage data for different emotional states. Our analysis demonstrates that emotion can be detected from the usage data up to a certain level. Moreover, our proposed classifier enables the best detection of five emotional states namely happiness, inspiration, sympathy, disgust, and fear compared to other existing classifiers. Besides, the analysis also reveals that user identification through usage dynamics does not result in a good level of accuracy when usage gets influenced by different emotional states.
THE TREATMENT OF ENCAPSULATED BRAIN ABSCESS

Although there has been advance in the treatment of brain abscess by modern methods, the mortality still remains strikingly higher than that reported by Macewen1in 1893. In recent years my associates and I have been using with slight modifications the method described by King2in 1924. This consists of direct transcortical exposure of the abscess, uncapping the presenting wall and packing of the cavity in one stage. The increased intracranial pressure then theoretically everts the abscess wall. Though we feel that this is the best method to date, we have had our share of failures, owing chiefly to technical difficulties arising in the treatment of deep-seated abscesses. The first of these difficulties lies in the fact that though the overlying brain is removed in the exposure of the abscess capsule there is still considerable trauma to the adjacent brain. The latter is not removed and may predispose
Improving on-line BIST-based diagnosis for roving STARs

We present improvements to our on-line BIST-based diagnosis technique originally used in the roving STARs approach. The enhanced technique starts with a new method of analyzing the BIST results, and employs the original divide-and-conquer method as a second phase only when the first phase fails or it does not achieve maximum diagnostic resolution. The combined technique significantly reduces the diagnosis time, improves the resolution in several cases, and also requires less fault-free resources.
MultiMo-Bat: A biologically inspired integrated jumping–gliding robot

This paper presents the design, development, and verification of a miniature integrated jumping and gliding robot, the MultiMo-Bat, which is inspired by the locomotion strategy of vampire bats. This 115.6 g robot exhibits high jumping and gliding performance, reaching heights of over 3 m, to overcome obstacles in the environment. The MultiMo-Bat was developed by a novel integrated design strategy that combines jumping and gliding locomotion modes and minimizes the necessary actuation and structural components by sharing a significant portion of the components required for each mode; nearly 70% of the total robot mass is utilized by both modes. This results in overall low mass, low volume, and high co-operation between the modes which allows for the preservation of over 80% of the performance of the independent jumping locomotion mode when combined. This not only allows for two high-performance locomotion modes, but also for all of the necessary actuation components to be on board. Key considerations and components of the design are discussed in the context of the integrated design approach. A prototype of the system is constructed and experimentally tested in various configurations to elucidate the overall system and integration performance. Finally, metrics are developed to begin to quantify the level and performance of the integrated approach as well as allow it to be compared to other mechanical and biological systems. This type of jumping and gliding robot can be used to explore, inspect, and monitor unstructured environments for security and environment monitoring applications.
A variational approach to simultaneous multi-object tracking and classification

Object tracking and classification serve as basic components for the different perception tasks of autonomous robots. They provide the robot with the capability of class-aware tracking and richer features for decision-making processes. The joint estimation of class assignments, dynamic states and data associations results in a computationally intractable problem. Therefore, the vast majority of the literature tackles tracking and classification independently. The work presented here proposes a probabilistic model and an inference procedure that render the problem tractable through a structured variational approximation. The framework presented is very generic, and can be used for various tracking applications. It can handle objects with different dynamics, such as cars and pedestrians and it can seamlessly integrate multi-modal features, for example object dynamics and appearance. The method is evaluated and compared with state-of-the-art techniques using the publicly available KITTI dataset.
Hybrid motion/force control of multi-backbone continuum robots

The recent growth of surgical applications exploiting continuum robots demands for new control paradigms that ensure safety by controlling interaction forces of tele-operated end-effectors. In this paper, we present the modeling, sensing and control of multi-backbone continuum robots in a unified framework for hybrid motion/force control. Multi-backbone continuum robots allow to estimate forces and torques at the operational point by monitoring loads along their actuation lines without the need for a dedicated transducer at the operational point. This capability is indeed crucial in emerging fields such as robotic surgery where cost and strict sterilization guidelines prevent the adoption of a dedicated sensor to provide force feedback from the sterile field. To advance further the force sensing capabilities of multi-backbone continuum robots, we present a new framework for hybrid motion and force control of continuum robots with intrinsic force sensing capabilities. The framework is based on a kinetostatic modeling of the multi-backbone continuum robot with, a simplified model for online estimate of the manipulator’s compliance, and a new strategy for merging force and motion control laws in the configuration space of the manipulator. Experimental results show the ability to sense and regulate forces at the operational point and evaluate the framework for shape exploration and stiffness imaging in flexible environments.
Search in JXTA and other distributed networks

The goal of this paper is to review and classify the different approaches to search in peer-to-peer networks. We then describe the approach implemented in JXTA search. JXTA is an open peer-to-peer network environment. JXTA search is a network of hubs that index the content of a peer-topeer network. Finally, we propose an organization of the JXTA search hubs, which reduces the storage and communication requirements between the hubs.
Reduced-complexity representation of the human arm active endpoint stiffness for supervisory control of remote manipulation

In this paper, a reduced-complexity model of the human arm endpoint stiffness is introduced and experimentally evaluated for the teleimpedance control of a compliant robotic arm. The modeling of the human arm endpoint stiffness behavior is inspired by human motor control principles on the predominant use of the arm configuration in directional adjustments of the endpoint stiffness profile, and the synergistic effect of muscular activations, which contributes to a coordinated modification of the task stiffness in all Cartesian directions. Calibration and identification of the model parameters are carried out experimentally, using perturbation-based arm endpoint stiffness measurements in different arm configurations and cocontraction levels of the chosen muscles. Consequently, the real-time model is used for the remote control of a compliant robotic arm while executing a drilling task, a representative example of tool use in environments with constraints and dynamic uncertainties. The results of this study illustrate that the proposed model enables the master to execute the remote task by modulation of the directions of the major axes of the endpoint stiffness ellipsoid and its volume using natural arm configurations and the cocontraction of the involved muscles, respectively.
SpinCouple: Development of a Web Tool for Analyzing Metabolite Mixtures via Two-Dimensional J-Resolved NMR Database.

A new Web-based tool, SpinCouple, which is based on the accumulation of a two-dimensional (2D) (1)H-(1)H J-resolved NMR database from 598 metabolite standards, has been developed. The spectra include both J-coupling and (1)H chemical shift information; those are applicable to a wide array of spectral annotation, especially for metabolic mixture samples that are difficult to label through the attachment of (13)C isotopes. In addition, the user-friendly application includes an absolute-quantitative analysis tool. Good agreement was obtained between known concentrations of 20-metabolite mixtures versus the calibration curve-based quantification results obtained from 2D-Jres spectra. We have examined the web tool availability using nine series of biological extracts, obtained from animal gut and waste treatment microbiota, fish, and plant tissues. This web-based tool is publicly available via http://emar.riken. jp/spincpl.
Mitochondrial Function and Dysfunction: An Update

With the current explosion of knowledge on the role of mitochondrial dysfunction in the genesis of various human disease states, there is an increased interest in targeting mitochondrial processes, pathways, and proteins for drug discovery efforts in cancer and cardiovascular, metabolic, and central nervous system diseases, the latter including autism and neurodegenerative diseases. We provide an update on understanding the central role of the mitochondrion in ATP and reactive oxygen species production and in controlling cell death pathways.
Multilevel polarization for nonbinary codes and parallel channels

We study polarization for nonbinary channels with input alphabet of size q = 2r, r = 2, 3, …. Using Arıkan's successive cancellation decoding, we prove that the virtual channels that arise in the process of polarization converge to q-ary channels with capacity 1, 2, …, r bits, and that the total transmission rate approaches the symmetric capacity of the channel. The multilevel polarization arising in this transmission represents a new phenomenon which is well suited to the description of dependent parallel channels that are subject to fading according to the order of their indices.
Pharmacologic Properties, Metabolism, and Disposition of Linaclotide, a Novel Therapeutic Peptide Approved for the Treatment of Irritable Bowel Syndrome with Constipation and Chronic Idiopathic Constipation

Linaclotide, a potent guanylate cyclase C agonist, is a therapeutic peptide approved in the United States for the treatment of irritable bowel syndrome with constipation and chronic idiopathic constipation. We present for the first time the metabolism, degradation, and disposition of linaclotide in animals and humans. We examined the metabolic stability of linaclotide in conditions that mimic the gastrointestinal tract and characterized the metabolite MM-419447 (CCEYCCNPACTGC), which contributes to the pharmacologic effects of linaclotide. Systemic exposure to these active peptides is low in rats and humans, and the low systemic and portal vein concentrations of linaclotide and MM-419447 observed in the rat confirmed both peptides are minimally absorbed after oral administration. Linaclotide is stable in the acidic environment of the stomach and is converted to MM-419447 in the small intestine. The disulfide bonds of both peptides are reduced in the small intestine, where they are subsequently proteolyzed and degraded. After oral administration of linaclotide, <1% of the dose was excreted as active peptide in rat feces and a mean of 3–5% in human feces; in both cases MM-419447 was the predominant peptide recovered. MM-419447 exhibits high-affinity binding in vitro to T84 cells, resulting in a significant, concentration-dependent accumulation of intracellular cyclic guanosine-3′,5′-monophosphate (cGMP). In rat models of gastrointestinal function, orally dosed MM-419447 significantly increased fluid secretion into small intestinal loops, increased intraluminal cGMP, and caused a dose-dependent acceleration in gastrointestinal transit. These results demonstrate the importance of the active metabolite in contributing to linaclotide’s pharmacology.
Manipulator Motion Planning in the Presence of Obstacles and Dynamic Constraints

Motion planning algorithms are traditionally restricted to finding spatial or "physical" paths only, while manipulator dynamics is ignored. The attendant low-level problem of timing and velocity along the path is left to the trajectory planner. In this study, these two aspects have been combined. The overall problem has been cast as an optimal control problem. The obstacle avoidance conditions have been for mulated as state-variable inequality constraints. These con straints are shown to be continuously differentiable in our formulation. The continuous-time problem is converted to a discrete-time problem to permit the use of nonlinear pro gramming algorithms for the heavily constrained problem. Computational issues such as discretization effects and al gorithmic efficiency have been addressed. Simulations are performed for the proposed method.
SACA: System-level Analog CIM Accelerators Simulation Framework: Accurate Simulation of Non-Ideal Components

Always-ON accelerators running TinyML applications are strongly limited by the memory and computation resources available in edge devices. Compute-In-Memory (CIM) architectures based on non-volatile memories (NVM) promise to bring the required compute and memory demands of Deep Neural Networks (DNN) to the edge while consuming extremely low power. However, their system-level design is constrained by the device and periphery noise which strongly impacts and compromises the accuracy of the DNN workload. In this paper SACA, a framework for simulating host & CIM accelerator systems, is presented. The simulator quantifies the system reliability by taking into account device-level non-idealities. The accuracy of two representative TinyML workloads is analyzed based on the crossbar characteristics -NVM technology, crossbar size, periphery characteristics. To demonstrate the capabilities of SACA, extensive experiments are carried out. We have characterized a convolutional network tackling CIFAR10 image classification and a fully connected network performing Human Activity Recognition. The results lead to optimal energy/performance/accuracy profiles, while the overall analysis highlights the dramatic effects of IR-drop on larger crossbars, degrading the system's accuracy and compromising its reliability.
TripVista: Triple Perspective Visual Trajectory Analytics and its application on microscopic traffic data at a road intersection

In this paper, we present an interactive visual analytics system, Triple Perspective Visual Trajectory Analytics (TripVista), for exploring and analyzing complex traffic trajectory data. The users are equipped with a carefully designed interface to inspect data interactively from three perspectives (spatial, temporal and multi-dimensional views). While most previous works, in both visualization and transportation research, focused on the macro aspects of traffic flows, we develop visualization methods to investigate and analyze microscopic traffic patterns and abnormal behaviors. In the spatial view of our system, traffic trajectories with various presentation styles are directly interactive with user brushing, together with convenient pattern exploration and selection through ring-style sliders. Improved ThemeRiver, embedded with glyphs indicating directional information, and multiple scatterplots with time as horizontal axes illustrate temporal information of the traffic flows. Our system also harnesses the power of parallel coordinates to visualize the multi-dimensional aspects of the traffic trajectory data. The above three view components are linked closely and interactively to provide access to multiple perspectives for users. Experiments show that our system is capable of effectively finding both regular and abnormal traffic flow patterns.
Business Simulation Game Development for Education and Training in Supply Chain Management

This paper presents a simulation-based business game for training and education in the area of supply chain management. It starts with a short review of existing simulation games used for training and education in supply chain management, which is followed by a brief description of the ECLIPS game that has been developed for providing an insight into various aspects of supply chain management, with opportunity to analyze different supply chain structures and control mechanisms. In particular, the application of the ECLIPS game to comparison of different supply chain inventory management policies, including non-cyclic and cyclic ones, is provided. Also, the paper presents a special computer-aided tool that allows testing and evaluating various scenarios of the ECLIPS game. The method of scenario evaluation is described as well.
HIS-388, a Novel Orally Active and Long-Acting 11β-Hydroxysteroid Dehydrogenase Type 1 Inhibitor, Ameliorates Insulin Sensitivity and Glucose Intolerance in Diet-Induced Obesity and Nongenetic Type 2 Diabetic Murine Models

11β-Hydroxysteroid dehydrogenase type 1 (11β-HSD1) is considered a potential therapeutic target in the treatment of type 2 diabetes mellitus. In this study, we investigated the pharmacological properties of HIS-388 (N-[(1R,2s,3S,5s,7s)-5-hydroxyadamantan-2-yl]-3-(pyridin-2-yl) isoxazole-4-carboxamide), a newly synthesized 11β-HSD1 inhibitor, using several mouse models. In cortisone pellet–implanted mice in which hypercortisolism and hyperinsulinemia occur, single administration of HIS-388 exhibited potent and prolonged suppression of plasma cortisol and lowered plasma insulin levels. These effects were more potent than those achieved using the same dose of other 11β-HSD1 inhibitors (carbenoxolone and compound 544 [3-[(1s,3s)-adamantan-1-yl]-6,7,8,9-tetrahydro-5H-[1,2,4]triazolo[4,3-a]azepine]), indicating that HIS-388 potently and continuously suppresses 11β-HSD1 enzyme activity in vivo. In diet-induced obese mice, HIS-388 significantly decreased fasting blood glucose, plasma insulin concentration, and homeostasis model assessment–insulin resistance score, and ameliorated insulin sensitivity. In addition, HIS-388 significantly reduced body weight and suppressed the elevation of blood glucose during the pyruvate tolerance test. In nongenetic type 2 diabetic mice with disease induced by a high-fat diet and low-dose streptozotocin, HIS-388 also significantly decreased postprandial blood glucose and plasma insulin levels and improved glucose intolerance. The effects of HIS-388 on glucose metabolism were indistinguishable from those of an insulin sensitizer, pioglitazone. Our results suggest that HIS-388 is a potent agent against type 2 diabetes. Moreover, amelioration of diabetic symptoms by HIS-388 was at least in part attributable to an antiobesity effect or improvement of hepatic insulin resistance. Therefore, potent and long-lasting inhibition of 11β-HSD1 enzyme activity may be an effective approach for the treatment of type 2 diabetes and obesity-associated disease.