Miracle-dz/UniFAR-FTUs huggingface dataset:
Protective effect of citrus lemon on inflammation and adipokine levels in acrylamide-induced oxidative stress in rats

1Nutrition and Metabolic Diseases Research Center, Ahvaz Jundishapur University of Medical Sciences, Ahvaz, Iran, 2Hyperlipidemia Research Center, Ahvaz Jundishapur University of Medical Sciences, Ahvaz, Iran, 3Department of Food Hygiene, Faculty of Veterinary Medicine, Shahid Chamran University of Ahvaz, Ahvaz, Iran, 4Department of Nutritional Science, Ahvaz Jundishapur University of Medical Sciences, Ahvaz, Iran
Guiding wiki crowds through resource scheduling

Wikis are among the most popular technologies for collaborative knowledge production. In brief, a wiki is a collaborative content creation system, where users contribute knowledge content in the form of articles, while they can also edit and even delete the contributions of others [1]. Wikis have received significant interest in the past few years and they are increasingly being used to support knowledge development in many domains, from education, to scientific research, and from activities of the public sector to enterprise environments. Last, one of the most well-known and studied wikis, the popular Wikipedia, is an ever-growing source of information with millions active users and articles. The rapid expansion and success of wikis is based on the open form of user collaboration that they are based on. That is, wiki users are free to edit any article they wish, with almost no restrictions on their access and edit rights. This open collaboration enables the massive production of wiki articles, which cover a broad spectrum of topics and expertise backgrounds. However, this same self-coordination poses significant limitations in terms of content quality. Take as an example Wikipedia: although it features a number of qualitative articles, it has also a very long tail of low-quality ones [2]. This inability to guarantee quality lowers the reliability of wikis and hinders their adoption. To guide the wiki crowd, systematize contributions and help them utilize their knowledge competencies more efficiently [3], we propose a coordination scheme that can be viewed as a scheduling problem [4]. The wiki is seen as a system with resources, which are the users and their expertise, and tasks, which are the wiki articles that need quality improvement. The objective is to match users to articles, in such a way as to maximize the average quality of the articles inside the wiki, regarding specific constraints such as user workload. The work is presented as follows: Section 2 formulates the problem and gives the methodology adopted to solve it. Section 3 shows some promising results. Last, Section 3 concludes the work and gives perspectives for the future. 6th Multidisciplinary International Conference on Scheduling : Theory and Applications (MISTA 2013) 27-29 August 2010, Gent, Belgium
The regulation of DIDS on PI3K/Akt and ROS signal transduction in the ischemia-reperfusion injury myocardium

Objective To investigate the regulation of DIDS on PI3K/Akt and ROS signal transduction in the ischemia-reperfusion injury myocardium. Methods Male SD rats were randomised into four groups sham group, I/RI (ischemia-reperfusion injury) group, CAT (catalase) group, and DIDS group. The myocardial infarction sise, the levels of tissue ROS, the myocardial apoptosis index, the serum levels of creatine kinase (CK) and lacate dehydrogenase (LDH), the activity of malonaldehyde (MDA) and superoxide dismutase (SOD), and the myocardial Akt and activity of malonaldehyde (MDA) and superoxide dismutase (SOD), and the myocardial Akt and phospho-Akt protein expressions were determined. Results (1) Compared with the I/RI group, the myocardial infarction sise, the apoptotic index, the activity of CK and LDH were significantly decreased in DIDS and CAT groups, and there was no difference between CAT and DIDS groups (p>0.05). (2) Compared with the I/RI group, the levels of MDA were decreased and the activity of SOD was increased in DIDS and CAT groups (p<0.05). The activity of SOD was higher, but the levels of MDA were lower in CAT group than DIDS group (p<0.05). (3) Compared with the I/RI group, the myocardial ROS levels were significantly reduced in DIDS and CAT groups. Moreover, CAT group had lower ROS levels than DIDS group (p<0.05). (4) There was no significant difference on the total Akt expression in the four groups (p>0.05). Compared with the sham group, the phospho-Akt levels were enhanced in the other three groups (p<0.05). The phospho-Akt levels were significantly higher in DIDS group than I/R and CAT groups, (p<0.05), but the levels of phospho-Akt were no difference between I/R and CAT group (p>0.05). Conclusion DIDS strongly protects cardiomyocytes against I/RI-induced apoptosis via activating PI3K/Akt signalling pathway and reducing ROS levels.
Phantom Vibration and Ringing is Linked to Poor Emotional Intelligence and Anxiety among Undergraduates

Mobile phone use has been linked to phantom vibration and ringing; however, the role that it plays in the mental health of young adults, who are known to be heavy users of mobile phones, remains unexplored. Therefore, the aim of the present study was to explore the prevalence of phantom vibration and ringing among undergraduates and examine the relationship between phantom vibration and ringing, emotional intelligence, and anxiety. Accordingly, a survey was conducted with 311 Chinese undergraduates who responded to a questionnaire about phantom vibration and ringing, and assessments that measure emotional intelligence and anxiety. The results showed that more than half the sample and approximately 37% of the participants had experienced phantom vibration and ringing, respectively. Although a large percentage of the undergraduate sample did not find phantom vibration and ringing to be bothersome, some students reported that it caused them anxiety. Taken together, these results suggest that excessive phone use might lead to misinterpretations of sensory signals. These findings serve as an evidence-based cautionary note against excessive reliance on mobile phones.
Running head: Personalized Avatars and Self-Presence 1 The Effect of Personalized Avatars on Self-Presence

In order to achieve a sense of self-presence in a virtual environment, users are represented by avatars. While avatars do not have to resemble individual users or even appear human, the avatar in which a user is embodied in can affect how that user behaves in a virtual environment. Thus, experiments in virtual reality will often manipulate avatar appearance, including personalizing avatars and agents so they resemble individual users. However, the customizable features in avatar creation software may create a biased representation of the participant. In the following paper, we discuss issues in generating custom avatars for experimental purposes and briefly describe the method we use of generating semi-customized avatars for use in a networked virtual environment designed for experimental manipulations. Using a small sample of convenience from an ongoing experiment, we describe participant self-presence ratings while inhabiting these avatars and compare those ratings to the “ground truth” ratings of avatar resemblance to the photographs by research assistant coders. We find a relationship between coder ratings of resemblance and participant ratings of self-presence for a subgroup of participants. Finally, we discuss suggested areas of improvement in avatar generation, including common pitfalls in photographing user faces and customizing avatar bodies and accessories.
Investigating the effects of dexamethasone on blood-brain barrier permeability and inflammatory response following focused ultrasound and microbubble exposure

Rationale: Clinical trials are currently underway to test the safety and efficacy of delivering therapeutic agents across the blood-brain barrier (BBB) using focused ultrasound and microbubbles (FUS+MBs). While acoustic feedback control strategies have largely minimized the risk of overt tissue damage, transient induction of inflammatory processes have been observed following sonication in preclinical studies. The goal of this work was to explore the potential of post-sonication dexamethasone (DEX) administration as a means to mitigate treatment risk. Vascular permeability, inflammatory protein expression, blood vessel growth, and astrocyte activation were assessed. Methods: A single-element focused transducer (transmit frequency = 580 kHz) and DefinityTM microbubbles were used to increase BBB permeability unilaterally in the dorsal hippocampi of adult male rats. Sonicating pressure was calibrated based on ultraharmonic emissions. Dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) was used to quantitatively assess BBB permeability at 15 min (baseline) and 2 hrs following sonication. DEX was administered following baseline imaging and at 24 hrs post-FUS+MB exposure. Expression of key inflammatory proteins were assessed at 2 days, and astrocyte activation and blood vessel growth were assessed at 10 days post-FUS+MB exposure. Results: Compared to saline-treated control animals, DEX administration expedited the restoration of BBB integrity at 2 hrs, and significantly limited the production of key inflammation-related proteins at 2 days, following sonication. Indications of FUS+MB-induced astrocyte activation and vascular growth were diminished at 10 days in DEX-treated animals, compared to controls. Conclusions: These results suggest that DEX provides a means of modulating the duration of BBB permeability enhancement and may reduce the risk of inflammation-induced tissue damage, increasing the safety profile of this drug-delivery strategy. This effect may be especially relevant in scenarios for which the goal of treatment is to restore or preserve neural function and multiple sonications are required.
Electrochemical Behavior of Valsartan, Glibenclamide and their Interaction with Each other Using Square Wave Voltammetry

In this work an electrochemical quantification and interaction of valsartan and glimepiride were studied on hanging mercury drop electrode (HMDE) using square wave voltammetric (SWV) technique. The effect of temperature on the interaction was investigated in eight degrees of heat and the thermodynamics parameters (enthalpy, entropy & free gibbs energy) were calculated for the interaction using Van't Hoff equation and binding constant (K) also obtained from interaction equation. From the values of the calculated thermodynamic parameters it found that the main bonding forces that predominated over the interaction were Vander Waals and Hydrogen bonding. The calibration curves of each drug was liner with R2 value equal to 0.9819, 0.997 and the limit of detection was found to be 4.99 x 10-7, 3.48 x 10-8 for valsartan and glimepiride respectively. Through the limit of detection, this method can be used as a standard method in estimating the pharmacists in pharmaceutics and verifying the credibility of the manufacturers of the two drugs.
Inflation Dynamics and Global Value Chains

The global economy has witnessed a decline in inflation and an increase in inflation synchronization since the early 1980s. This paper investigates the relationship between inflation synchronization and trade integration, and documents the strong link between inflation co-movement and Global Value Chain (GVC) participation. Using 35 years and both gross and value-added trade flows, evidence shows that an increase in production linkages, as proxied by trade in intermediate inputs, is strongly associated with higher inflation correlation. Moreover, backward GVC participation is associated with an increase in bilateral inflation co-movement while forward participation is linked with a higher correlation between domestic and worldwide inflation. The paper also finds evidence of the effect of trade integration in decreasing inflation levels.
SERAD: Soft Error Resilient Asynchronous Design Using a Bundled Data Protocol

The risk of soft errors due to radiation continues to be a significant challenge for engineers trying to build systems that can handle harsh environments. Building systems that are Radiation Hardened by Design (RHBD) is the preferred approach, but existing techniques are expensive in terms of performance, power, and/or area. This paper introduces a novel soft-error resilient asynchronous bundled-data design template, SERAD, which uses a combination of temporal and spatial redundancy to mitigate Single Event Transients (SETs) and upsets (SEUs). SERAD uses Error Detecting Logic (EDL) to detect SETs at the inputs of sequential elements and correct them via re-sampling. Because SERAD only pays the delay penalty in the presence of an SET, which rarely occurs, its average performance is comparable to the baseline synchronous design. We tested the SERAD design using a combination of Spice and Verilog simulations and evaluated its impact on area, frequency, and power on an open-core MIPS-like processor using a NCSU 45nm cell library. Our post-synthesis results show that the SERAD design consumes less than half of the area of the Triple Modular Redundancy (TMR), exhibits significantly less performance degradation than Glitch Filtering (GF), and consumes no more total power than the baseline unhardened design.
An extended quantum process algebra (eQPAlg) approach for distributed quantum systems

In this work, we have expounded the communication procedure of quantum systems by means of process algebra. The main objective of our research effort is to formally represent the communication between distributed quantum systems. In this new proposed communication model we have ameliorated the existing rules of Lalire's quantum process algebra QPAlg. We have brought some important modification in QPAlg by introducing the concept of formally specifying the Quantum teleportation protocol. We have further introduced the formal description of protocol by using programs that best explains its working and satisfies the specification. Examples have been provided to describe the working of the improved algebra that formally explain the sending and receiving of both classical as well as quantum data, keeping in mind the principal features of quantum mechanics.
A Novel Inspection System For Variable Data Printing Using Deep Learning

We present a novel approach for inspecting variable data prints (VDP) with an ultra-low false alarm rate (0.005%) and potential applicability to other real-world problems. The system is based on a comparison between two images: a reference image and an image captured by low-cost scanners. The comparison task is challenging as low-cost imaging systems create artifacts that may erroneously be classified as true (genuine) defects. To address this challenge we introduce two new fusion methods, for change detection applications, which are both fast and efficient. The first is an early fusion method that combines the two input images into a single pseudo-color image. The second, called Change-Detection Single Shot Detector (CD-SSD) leverages the SSD by fusing features in the middle of the network. We demonstrate the effectiveness of the proposed deep learning-based approach with a large dataset from real-world printing scenarios. Finally, we evaluate our models on a different domain of aerial imagery change detection (AICD). Our best method clearly outperforms the state-of-the-art baseline on this dataset.
WICA: nonlinear weighted ICA

Independent Component Analysis (ICA) aims to find a coordinate system in which the components of the data are independent. In this paper we construct a new nonlinear ICA model, called WICA, which obtains better and more stable results than other algorithms. A crucial tool is given by a new efficient method of verifying nonlinear dependence with the use of computation of correlation coefficients for normally weighted data.
Symmetry-dependent control of a spin qubit in lateral GaAs quantum dot

We study the influence of quantum dot symmetry on the Rabi frequency and phonon induced spin relaxation rate in a single electron GaAs spin qubit. We find that anisotropic dependence on the magnetic field direction is independent of the choice of the gating potential. Also, we discover that relative orientation of the quantum dot, with respect to the crystallographic frame, is relevant in systems with ${\bf C}_{1{\rm v}}$, ${\bf C}_{2{\rm v}}$, or ${\bf C}_{n}$ ($n\neq4r$) symmetry. To demonstrate the important impact of the gating potential shape on the spin qubit lifetime, we compare the effects of an equilateral triangle, square, and rectangular confinement with the known results for the harmonic potential. In the studied cases, enhanced spin qubit lifetime is revealed, reaching almost six orders of magnitude increase for the equilateral triangle gating.
Towards Generalizable Surgical Activity Recognition Using Spatial Temporal Graph Convolutional Networks

Modeling and recognition of surgical activities poses an interesting research problem. Although a number of recent works studied automatic recognition of surgical activities, generalizability of these works across different tasks and different datasets remains a challenge. We introduce a modality that is robust to scene variation, and that is able to infer part information such as orientational and relative spatial relationships. The proposed modality is based on spatial temporal graph representations of surgical tools in videos, for surgical activity recognition. To explore its effectiveness, we model and recognize surgical gestures with the proposed modality. We construct spatial graphs connecting the joint pose estimations of surgical tools. Then, we connect each joint to the corresponding joint in the consecutive frames forming inter-frame edges representing the trajectory of the joint over time. We then learn hierarchical spatial temporal graph representations using Spatial Temporal Graph Convolutional Networks (ST-GCN). Our experiments show that learned spatial temporal graph representations perform well in surgical gesture recognition even when used individually. We experiment with the Suturing task of the JIGSAWS dataset where the chance baseline for gesture recognition is 10%. Our results demonstrate 68% average accuracy which suggests a significant improvement. Learned hierarchical spatial temporal graph representations can be used either individually, in cascades or as a complementary modality in surgical activity recognition, therefore provide a benchmark for future studies. To our knowledge, our paper is the first to use spatial temporal graph representations of surgical tools, and pose-based skeleton representations in general, for surgical activity recognition.
Resource Sharing in the Edge: A Distributed Bargaining-Theoretic Approach

The growing demand for edge computing resources, particularly due to increasing popularity of Internet of Things (IoT), and distributed machine/deep learning applications poses a significant challenge. On the one hand, certain edge service providers (ESPs) may not have sufficient resources to satisfy their applications according to the associated service-level agreements. On the other hand, some ESPs may have additional unused resources. In this paper, we propose a resource-sharing framework that allows different ESPs to optimally utilize their resources and improve the satisfaction level of applications subject to constraints such as communication cost for sharing resources across ESPs. Our framework considers that different ESPs have their own objectives for utilizing their resources, thus resulting in a multi-objective optimization problem. We present an ${N}$ -person Nash Bargaining Solution (NBS) for resource allocation and sharing among ESPs with Pareto optimality guarantee. Furthermore, we propose a distributed, primal-dual algorithm to obtain the NBS by proving that the strong-duality property holds for the resultant resource sharing optimization problem. Using synthetic and real-world data traces, we show numerically that the proposed NBS based framework not only enhances the ability to satisfy applications’ resource demands, but also improves utilities of different ESPs.
Reachability in fixed dimension vector addition systems with states

The reachability problem is a central decision problem for formal verification based on vector addition systems with states (VASS), which are equivalent to Petri nets and form one of the most studied and applied models of concurrency. Reachability for VASS is also inter-reducible with a plethora of problems from a number of areas of computer science. In spite of recent progress, the complexity of the reachability problem remains unsettled, and it is closely related to the lengths of shortest VASS runs that witness reachability. We consider VASS of fixed dimension, and obtain three main results. For the first two, we assume that the integers in the input are given in unary, and that the control graph of the given VASS is flat (i.e., without nested cycles). We obtain a family of VASS in dimension 3 whose shortest reachability witnessing runs are exponential, and we show that the reachability problem is NP-hard in dimension 7. These results resolve negatively questions that had been posed by the works of Blondin et al. in LICS 2015 and Englert et al. in LICS 2016, and contribute a first construction that distinguishes 3-dimensional flat VASS from 2-dimensional VASS. Our third result, by means of a novel family of products of integer fractions, shows that 4-dimensional VASS can have doubly exponentially long shortest reachability witnessing runs. The smallest dimension for which this was previously known is 14.
Fulminant soft-tissue extension of anaplastic multiple myeloma masquerading as postoperative abscess

M ultiple myeloma is a malignant plasma cell dyscrasia that originates within medullary bone. Anaplastic myeloma is a particularly aggressive subtype that can affect extramedullary locations. Orthopaedic surgeons typically treat impending or actual pathologic fractures in patients with multiple myeloma. We report a patient with anaplastic multiple myeloma who developed what was believed to be an infection after intramedullary nailing of an impending femoral fracture. Her final diagnosis, however, was massive extramedullary extension of primary disease affecting the hip and thigh. This case illustrates the importance of maintaining a differential diagnosis to include both infectious and neoplastic etiologies when treating postsurgical oncology patients, so as to follow the adage, ‘‘Culture what you biopsy and biopsy what you culture. ’’ Our institutional review board exempts case reports from the approval process. The patient signed informed consent for publication.
A quantum-classical cloud platform optimized for variational hybrid algorithms

In order to support near-term applications of quantum computing, a new compute paradigm has emerged—the quantum-classical cloud—in which quantum computers (QPUs) work in tandem with classical computers (CPUs) via a shared cloud infrastructure. In this work, we enumerate the architectural requirements of a quantum-classical cloud platform, and present a framework for benchmarking its runtime performance. In addition, we walk through two platform-level enhancements, parametric compilation and active qubit reset, that specifically optimize a quantum-classical architecture to support variational hybrid algorithms, the most promising applications of near-term quantum hardware. Finally, we show that integrating these two features into the Rigetti Quantum Cloud Services platform results in considerable improvements to the latencies that govern algorithm runtime.