Miracle-dz/UniFAR-FTUs huggingface dataset:
TNF-α Autocrine Feedback Loops in Human Monocytes: The Pro- and Anti-Inflammatory Roles of the TNF-α Receptors Support the Concept of Selective TNFR1 Blockade In Vivo

Selective TNFR1 blockade in inflammatory diseases is emerging as a clinical strategy. We studied the roles of the two TNF-α receptors, TNFR1 and TNFR2, in human monocytes, the principal producer of TNF-α and central to many TNF-α driven diseases. We hypothesised that TNF-α has pro- and anti-inflammatory effects on monocytes, occurring differentially via TNFR1 and TNFR2. Monocytes were isolated from healthy human subjects and exposed to LPS, plus/minus the addition of blocking antibodies to TNF-α or its receptors. Pro- and anti-inflammatory cytokine production was quantified using real-time PCR and ELISAs. Cell surface expression of TNFR1/2 was measured by flow cytometry. We demonstrated that monocytes vary in the expression patterns of TNFR1 and TNFR2. Autocrine binding of TNF-α led to sustained upregulation of proinflammatory cytokines via TNFR1. In contrast, autocrine binding via TNFR2 upregulated the anti-inflammatory cytokine, IL-10, without proinflammatory effect. TNFR2 was responsible for binding soluble TNF-α secreted by monocytes, clearing the cytokine from the pericellular environment. TNFR1 blockade did not change the cell surface expression of TNFR2, leaving this receptor free to upregulate IL-10. These novel results support the concept of selective TNFR1 blockade in vivo in order that positive anti-inflammatory effects of TNF-α can be retained via TNFR2 ligation.
An efficient object discovery and selection protocol in 3D streaming-based systems over thin mobile devices

3D streaming over thin mobile devices is considered challenging due to the mobile devices' limited capabilities such as limited energy lifetime, processing power, storage capacity, and graphics' hardware and accelerator capabilities, that make it very difficult for mobile devices to render and process large and complex 3D scenes. To address this issue, 3D streaming techniques have been proposed that aim at reducing the resolution of 3D objects to make it easy to deliver and render. However, streaming all of the 3D objects in a given virtual environment (VE) is not considered efficient. In this paper, we propose a novel object selection technique for 3D streaming based systems over thin mobile devices, which we refer to as OCTET. Our protocol, which is based on multi-level area of interest (AOI), allows for the selection of the 3D objects required for the user's virtual scene, taking into account the user's interests, the location of the 3D objects in the multi-level AOI, and the mobile device's available resources.
FSaaS: File System as a Service

Cloud-based object storage is provided as a cost-efficient, scalable, and durable service for accessing and storing objects through web technologies. With years of development and successful deployment, it has been widely adopted by individuals and organizations. Besides its advantages, there are several major concerns, such as, manageability, operation performance from a user perspective, convenience of access, and vendor lock-in. In this project, we have developed a File System as a Service (FSaaS) to address the aforementioned concerns. The FSaaS design is centred around separating file operations into groups and treating each operation group differently. We deal with the file system structures and attributes of objects in FSaaS, and leave the back-end storage as flat, and we provide a set of connector services that support various types of cloud storage for asynchronous operation mode. This separation of meta-data and use of connector services allow fast searching, transparent access, authentication simplification, concurrent operation, and load-balancing. The evaluation demonstrates that FSaaS can significantly improve user experience, boost operation performance, and reduce object operational delay. The scalability and flexibility of the FSaaS are also demonstrated via asynchronous operation mode.
Terminally differentiated neutrophils predominantly express Survivin‐2α, a dominant‐negative isoform of Survivin

Survivin, which is a member of the inhibitor of apoptosis protein family, was found originally in immature cells and cancer cells but not in non‐neoplastic adult tissues. The subsequent identification of four other alternative splice variants that possess distinct functions and localizations suggested the diverse roles of survivin isoforms. An unspecified isoform of survivin was found recently to be induced in terminally differentiated neutrophils by cytokines that prolong the neutrophil lifespan, such as GM‐CSF and G‐CSF, suggesting the importance of survivin in blocking apoptosis in neutrophils. To examine the mechanism by which survivin inhibits neutrophil apoptosis, we attempted to induce survivin by GM‐CSF/G‐CSF in an HL60 cell line that was differentiated into neutrophils by all‐trans retinoic acid and DMSO and freshly isolated human neutrophils. The antiapoptotic isoform “Survivin,” which was decreased during differentiation, was re‐induced by GM‐CSF in neutrophil‐like, differentiated HL60. In contrast, in normal neutrophils, survivin mRNA was observed to increase spontaneously after 24 h incubation, and no additional elevation was induced by GM‐CSF/G‐CSF, which exerted their antiapoptotic effects on the neutrophils in 6 h, despite the lack of survivin induction. PCR and Western blotting detected Survivin‐2α, a dominant‐negative of antiapoptotic Survivin, with no other isoforms in the freshly isolated or incubated neutrophils. Our study revealed that the expressed isoforms and the response to GM‐CSF were different between the HL60‐derived and normal neutrophils, which predominantly expressed Survivin‐2α, not likely involved in apoptosis inhibition by GM‐CSF/G‐CSF.
Markov Chain Modeling of Intermittency Chaos and Its Application to Hopfield NN

SUMMARY In this study, a modeling method of the intermittency chaos using the Markov chain is proposed. The performances of the intermittency chaos and the Markov chain model are investigated when they are injected to the Hopfield Neural Network for a quadratic assignment problem or an associative memory. Computer simulated results show that the proposed modeling is good enough to gain similar performance of the intermittency chaos.
Belief Propagation Guided Decimation Fails on Random Formulas

Let Φ be a uniformly distributed random k-SAT formula with n variables and m clauses. Nonconstructive arguments show that Φ is satisfiable for clause/variable ratios m/n ⩽ rk− SAT ∼ 2kln 2 with high probability. Yet no efficient algorithm is known to find a satisfying assignment beyond m/n ∼ 2kln (k)/k with a nonvanishing probability. On the basis of deep but nonrigorous statistical mechanics ideas, a message passing algorithm called Belief Propagation Guided Decimation has been put forward (Mézard, Parisi, Zecchina: Science 2002; Braunstein, Mézard, Zecchina: Random Struc. Algorithm 2005). Experiments suggested that the algorithm might succeed for densities very close to rk− SAT for k = 3, 4, 5 (Kroc, Sabharwal, Selman: SAC 2009). Furnishing the first rigorous analysis of this algorithm on a nontrivial input distribution, in the present article we show that Belief Propagation Guided Decimation fails to solve random k-SAT formulas already for m/n = O(2k/k), almost a factor of k below the satisfiability threshold rk− SAT. Indeed, the proof refutes a key hypothesis on which Belief Propagation Guided Decimation hinges for such m/n.
Self-Contained Ranging Sensor Aided Autonomous Guidance, Navigation, and Control for Indoor Flight

This paper describes the design and ﬂight test of a completely self-contained autonomous indoor Miniature Unmanned Aerial System (M-UAS). Guidance, navigation, and control algorithms are presented, enabling the M-UAS to autonomously explore cluttered indoor areas without relying on any oﬀ-board computation or external navigation aids such as GPS. The system uses a scanning laser rangeﬁnder and a streamlined Simultaneous Localization and Mapping (SLAM) algorithm to provide a position and heading estimate, which is combined with other sensor data to form a six degree-of-freedom inertial navigation solution. This enables an accurate estimate of the vehicle attitude, relative position, and velocity. The state information, with a self-generated map, is used to implement a frontier-based exhaustive search of an indoor environment. Improvements to existing guidance algorithms balance exploration with the need to remain within sensor range of indoor structures such that the SLAM algorithm has suﬃcient information to form a reliable position estimate. A dilution of precision metric is developed to quantify the eﬀect of environment geometry on the SLAM pose covariance, which is then used to update the 2-D position and heading in the navigation ﬁlter. Simulation and ﬂight test results validate the presented algorithms.
Endogenous fluctuations in the demand for education

Abstract. Enrollment rates to higher education reveal a quite large variation over time which cannot be explained by productivity shocks alone. We develop a human capital investment model in an overlapping generations framework that features endogenous fluctuations in the demand for education. Agents are heterogeneous in their beliefs about future wage differentials. An evolutionary competition between the heterogeneous beliefs determines the fraction of the newborn generation having a certain belief. Costly access to information on the returns to education induces agents to use potentially destabilizing backward looking prediction rules. Only if previous generations experience regret about their human capital investment decisions, will agents choose a more sophisticated prediction rule that dampens the cycle. Access to information becomes key for stable flows to higher education.
Coordinate Transformation is First Completed Downstream of Primary Motor Cortex

It was suggested previously that the transformation of action to muscle-based coding is completed in the primary motor cortex (M1). This is consistent with a predominant direct pathway leading from M1 to motoneurons. Accordingly, spinal segmental interneurons that are located downstream to M1 are expected to show muscle-like coding properties. We addressed this hypothesis using simultaneous recording of cortical and spinal activity in primates performing an isometric wrist task with multiple targets and two hand postures. Here we show that while the motor cortex follows an intermediate coordinate frame, spinal interneurons already follow a muscle-like coordinate frame. We thus suggest that the final steps in coordinate transformation of motor commands take place downstream of M1 via corticospinal interactions.
Securely Outsourced Face Recognition under Federated Cloud Environment

Computations over biometric data performed on untrusted cloud environment raises important concerns about the privacy of biometrics data. Face recognition has been widely applied in a variety of enterprise, civilian and law enforcement. Many schemes for privacy-preserving face recognition (PPFR) have been investigated over the past decade. In order to protect individuals' privacy, face recognition is performed over encrypted face images. However, these results increase the computation cost of the client and the face database owners with limited computing and storage resources. To overcome this kind of issue and to take benefits of cloud computing, outsourcing such tasks to the cloud environment has recently gained special attention. Currently, no secure techniques for outsourcing face biometric recognition are readily available to make client and the face database owners free from encryption and decryption operations. We consider the scenario where a client and a database owner of face images securely outsource their data to the cloud and ask the cloud to perform the face recognition task on their combined data in a privacy-preserving manner. We term such a process as privacy-preserving and outsourced face recognition (PPOFR). We propose a novel and efficient scheme to the PPOFR problem with outsourced computation for the first time under a federated cloud environment based on the Eigenfaces algorithm, which efficiently protects data confidentiality of the participating entities under the standard semi-honest model. To the best of our knowledge, ours is the first work to discuss and propose a comprehensive solution to the PPOFR problem that incurs negligible cost on the participating entities. We theoretically estimate both the computation and communication costs of the proposed protocol.
Understanding the facilitators and barriers to participation in people with acquired cognitive impairment

The International Classification of Functioning, Disability and Health (ICF) model of disability holds that both personal and environmental factors predict participation. However, little is known about these predictors for people with dementia. Similarly, ‘partnership between patients and clinicians in research’ is a stated aim of UK government policy but little is known about what facilitates this in the dementia population, particularly with respect to peer research. This thesis sought to throw light on both areas. Part 1 comprises a systematic review of research about factors associated with social participation by adults with acquired cognitive impairment. Results showed that, in some studies, psychological factors (e.g. self-efficacy) social factors (e.g. caregiver functioning or social support), and societal factors (e.g. the built environment), and transport were associated with social participation. Part 2 comprises an interview-based, qualitative, empirical study of different perspectives regarding the facilitators and barriers to people with dementia (PWD) doing peer research. Findings highlighted multiple factors that facilitated or hindered this activity: assumptions and language, adapting activity to the needs and abilities of PWD, perceptions of danger and opportunities for building trust, and motivations. Part 3 comprises a critical appraisal of issues encountered in the course of carrying out this research. Topics discussed include: personhood versus citizenship, insider research, creating the topic guide and defining peer research.
Metabolic phenotyping and systems biology approaches to understanding neurological disorders

The development of high-throughput metabolic profiling and the study of the metabolome are particularly important in brain research where small molecules or metabolites play fundamental signalling roles: neurotransmitters, signalling lipids, osmolytes and even ions. Metabolic profiling has shown that metabolic perturbations in the brain go beyond alterations of neurotransmission and that variations in brain metabolic homeostasis are associated with neurological disorders. In this report, we will focus on recent developments in the field of metabolic phenotyping that have contributed to unravelling the pathophysiology of neurological diseases. Also, we will highlight the necessity of implementing systems biology approaches to integrate metabolic data and tackle the structural and functional complexity of the brain in normal and pathological conditions.
Analysis of Goldbeter-Koshland Switch Using the Chemical Master Equation

The chemical master equation is considered as an accurate description of general chemical systems, and especially so for modeling gene regulatory networks and protein-protein interaction networks. This paper examines some “off-the-shelf” numerical approaches to solve the chemical master equation for the Goldbeter-Koshland switch on both sequential and parallel machines. The numerical results show that for moderate sized problems, some numerical approaches perform better than MonteCarlo algorithms. However, to solve even larger models more efficiently, special approximation techniques at the model/numerical level may be required. Numerical methods for the steady state solutions are also discussed here.
Measurement of arterial oxygen saturation (SpO2) using PPG optical sensor

The pulse oximeters are used to measure the heart rate and arterial oxygen saturation (SpO2). The photoplethysmographic (PPG) signals from pulse oximeters are highly influenced by the noise generated due to movement. The signal is also affected by the ambience light signal. It is essential to obtain a clean signal for the measurement of arterial oxygen saturation (SpO2). In this paper, an Adaptive Noise Cancelling (ANC) technique is being used to remove noise from the signal. A tri-axial based accelerometer data is also taken during the data acquisition time. Normalized Least Mean Square (NLMS) based adaptive filter algorithm is adopted. Tri-axis accelerometer data gives the directional data along the entire three axes. They are summed up and they are fed into the adaptive filter as reference noise signal. In the filter, the coefficients are updated based on the error signal and they are updated till the error becomes minimum. From the obtained clean signal oxygen saturation is calculated by finding the normalized ratio of ratios. Accelerometer based adaptive noise cancellation is found to reduce the errors in arterial oxygen saturation. The mean result for the mentioned algorithm is around 0.2409. The result is also found to be in correlation with the reference pulse oximeter.
Differential effects of brain-derived neurotrophic factor and neurotrophin-3 on hindlimb function in paraplegic rats

We compared the effect of viral administration of brain‐derived neurotrophic factor (BDNF) or neurotrophin 3 (NT‐3) on locomotor recovery in adult rats with complete thoracic (T10) spinal cord transection injuries, in order to determine the effect of chronic neurotrophin expression on spinal plasticity. At the time of injury, BDNF, NT‐3 or green fluorescent protein (GFP) (control) was delivered to the lesion via adeno‐associated virus (AAV) constructs. AAV–BDNF was significantly more effective than AAV–NT‐3 in eliciting locomotion. In fact, AAV–BDNF‐treated rats displayed plantar, weight‐supported hindlimb stepping on a stationary platform, that is, without the assistance of a moving treadmill and without step training. Rats receiving AAV–NT‐3 or AAV–GFP were incapable of hindlimb stepping during this task, despite provision of balance support. AAV–NT‐3 treatment did promote the recovery of treadmill‐assisted stepping, but this required continuous perineal stimulation. In addition, AAV–BDNF‐treated rats were sensitized to noxious heat, whereas AAV–NT‐3‐treated and AAV–GFP‐treated rats were not. Notably, AAV–BDNF‐treated rats also developed hindlimb spasticity, detracting from its potential clinical applicability via the current viral delivery method. Intracellular recording from triceps surae motoneurons revealed that AAV–BDNF significantly reduced motoneuron rheobase, suggesting that AAV–BDNF promoted the recovery of over‐ground stepping by enhancing neuronal excitability. Elevated nuclear c‐Fos expression in interneurons located in the L2 intermediate zone after AAV–BDNF treatment indicated increased activation of interneurons in the vicinity of the locomotor central pattern generator. AAV–NT‐3 treatment reduced motoneuron excitability, with little change in c‐Fos expression. These results support the potential for BDNF delivery at the lesion site to reorganize locomotor circuits.
Hilbert Huang transform based speech recognition

In today's world, to make man-machine interaction more effective speech recognition plays an important role in speech processing. This paper presents the application of Hilbert-Huang transform (HHT), a mathematical tool applied for feature extraction phase of the speech signal processing. These features are modeled and evaluated using Vector Quantization(VQ) and Fuzzy C Means(FCM) techniques. The proposed system highlights the importance of Discrete Cosine Transformation(DCT) applied for Hilbert Huang Transform to extract the better speech signal parameters. The features obtained from this process has better recognition accuracies. It also demonstrates the efficiency of DCT with HHT for FCM clustering technique over the VQ technique. The performance of HHT- FCM is discussed with the termination criteria `ε' and fuzzifier `m' parameters of FCM.
Question-Negotiation and Information Seeking in Libraries

Seekers of information in libraries either go through a librarian intermediary or they help themselves. When they go through librarians they must develop their questions through four levels of need, referred to here as the visceral, conscious, formalized, and compromised needs. In his pre-search interview with an information-seeker the reference librarian attempts to help him arrive at an understanding of his “compromised” need by determining: (1) the subject of his interest; (2) his motivation; (3) his personal characteristics; (4) the relationship of the inquiry to file organization; and (5) anticipated answers. The author contends that research is needed into the techniques of conducting this negotiation between the user and the reference librarian.
Genetic Variability For Different Biometrical Traits In Pearl Millet Genotypes ( Pennisetum glaucum

Pearl millet (Pennisetum glaucum (L.) R. Br. ) is an important crop of the semi-arid tropics in Africa and India. The present study was conducted to evaluate the pearl millet genotypes to assess the magnitude of variability and to understand the heritable component of variation present in the biometrical characters. A field trial was laid out with 47 pearl millet genotypes and the observations were recorded on days to 50% flowering, plant height, number of tillers per plant, ear head length, ear head breadth, root length, shoot length, root shoot ratio and seed yield per plant. The phenotypic co-efficient of variation (PCV) was greater than genotypic co-efficient of variation (GCV) for all the characters studied, this shows the influence of the environmental effect on the characters. The traits, number of tillers per plant, ear head length, root-shoot ratio and seed yield showed moderate PCV and GCV while the traits, days to 50% flowering, plant height, ear head breadth, root length and shoot length showed low PCV and GCV. High heritability was observed for all the traits under study. High heritability combined with high genetic advance (as per cent of mean) was observed for ear head length and seed yield and these characters were controlled by additive gene effects. Selection based on these characters would be effective for future pearl millet crop improvement programme.
Factors contributing to the retention of natural mentors among underrepresented students across the first year of college

Abstract The current study examined characteristics of natural mentoring relationships (NMRs; i.e. mentoring relationships that develop organically with adults in one’s pre-existing social network) among underrepresented college students as contributors to NMR retention across the first year of college. The sample consisted of 209 underrepresented college students (73% female; mean age = 18.1, SD = .35) who reported having a natural mentor during the first semester of college. Each participant could report up to five natural mentors and a total of 550 NMRs were reported. We found that more frequent contact and greater relational closeness with natural mentors during the Fall semester of mentees’ first year of college increased the likelihood that NMRs were retained through the Spring semester of the first year. These findings shed light on aspects of NMRs that may be most central to fostering their duration during difficult transitional spaces.