Miracle-dz/UniFAR-FTUs huggingface dataset:
Effect of Soaping Process on Crimp Properties of Optim Wool

Optim fiber is a kind of modified wool fiber by physical stretching of fine wool fiber, which changes the crimp ratio of the original wool. The effect of the soaping parameters, such as caustic concentration, temperature, treating time on Optim fiber crimp ratio was studied. The results showed that under the same caustic concentration, the crimp ratio is distinctly increased along with the temperature increase when the temperature is under 75 oC. However, when the temperature was higher than 75 oC, the crimp ratio started to reduce fast. Under the same soaping temperature, the caustic concentration change did not have the obvious effect on the crimp ratio change. When the temperature was above 80 oC, the crimp ratio reduced as a whole along with the caustic concentration. The change of the curl ratio was not obvious at the same caustic concentration within 20 min. However, the curl ratio reduced slowly with increasing the soaping time. At the same soaping time, the curl ratio of fibers reduced with increasing concentration of soaping. It could provide some technical reference for dyeing of optim fiber.
Interactions of the COP9 Signalosome with the E3 Ubiquitin Ligase SCFTIR1 in Mediating Auxin Response

The COP9 signalosome is an evolutionary conserved multiprotein complex of unknown function that acts as a negative regulator of photomorphogenic seedling development in Arabidopsis. Here, we show that plants with reduced COP9 signalosome levels had decreased auxin response similar to loss-of-function mutants of the E3 ubiquitin ligase SCFTIR1. Furthermore, we found that the COP9 signalosome and SCFTIR1 interacted in vivo and that the COP9 signalosome was required for efficient degradation of PSIAA6, a candidate substrate of SCFTIR1. Thus, the COP9 signalosome may play an important role in mediating E3 ubiquitin ligase–mediated responses.
Computing and Stability in Cortical Networks

Cortical neurons are predominantly excitatory and highly interconnected. In spite of this, the cortex is remarkably stable: normal brains do not exhibit the kind of runaway excitation one might expect of such a system. How does the cortex maintain stability in the face of this massive excitatory feedback? More importantly, how does it do so during computations, which necessarily involve elevated firing rates? Here we address these questions in the context of attractor networksnetworks that exhibit multiple stable states, or memories. We find that such networks can be stabilized at the relatively low firing rates observed in vivo if two conditions are met: (1) the background state, where all neurons are firing at low rates, is inhibition dominated, and (2) the fraction of neurons involved in a memory is above some threshold, so that there is sufficient coupling between the memory neurons and the background. This allows dynamical stabilization of the attractors, meaning feedback from the pool of background neurons stabilizes what would otherwise be an unstable state. We suggest that dynamical stabilization may be a strategy used for a broad range of computations, not just those involving attractors.
Accuracy vs. efficiency trade-offs in probabilistic diagnosis

This paper studies the accuracy/efficiency trade-off in probabilistic diagnosis formulated as finding the <i>most-likely explanation (MPE)</i> in a Bayesian network. Our work is motivated by a practical problem of efficient real-time fault diagnosis in computer networks using test transactions, or <i>probes</i>, sent through the network. The key efficiency issues include both the cost of probing (e.g., the number of probes), and the computational complexity of diagnosis, while the diagnostic accuracy is crucial for maintaining high levels of network performance. Herein, we derive a lower bound on the diagnostic accuracy that provides necessary conditions for the number of probes needed to achieve an asymptotically error-free diagnosis as the network size increases, given prior fault probabilities and a certain level of noise in probe outcomes. Since the exact MPE diagnosis is generally intractable in large networks, we investigate next the accuracy/efficiency trade-offs for very simple and efficient <i>local</i> approximation techniques, based on variable-elimination (the mini-bucket scheme). Our empirical studies show that these approximations "degrade gracefully" with noise and often yield an optimal solution when noise is low enough, and our initial theoretical analysis explains this behavior for the simplest (greedy) approximation. These encouraging results suggest the applicability of such approximations to certain almost-deterministic diagnostic problems that often arise in practical applications.
Optimal Inequalities in Probability Theory: A Convex Optimization Approach

We propose a semidefinite optimization approach to the problem of deriving tight moment inequalities for $P(X\in S)$, for a set S defined by polynomial inequalities and a random vector X defined on $\Omega\subseteq {\cal R}^n$ that has a given collection of up to kth-order moments. In the univariate case, we provide optimal bounds on $P(X\in S)$, when the first k moments of X are given, as the solution of a semidefinite optimization problem in k + 1 dimensions. In the multivariate case, if the sets S and $\Omega$ are given by polynomial inequalities, we obtain an improving sequence of bounds by solving semidefinite optimization problems of polynomial size in n, for fixed k. We characterize the complexity of the problem of deriving tight moment inequalities. We show that it is NP-hard to find tight bounds for $k\geq 4$ and $\Omega={\cal R}^n$ and for $k\geq 2$ and $\Omega={\cal R}^n_+,$ when the data in the problem is rational. For k = 1 and $\Omega={\cal R}^n_+$ we show that we can find tight upper bounds by solving n convex optimization problems when the set S is convex, and we provide a polynomial time algorithm when S and $\Omega$ are unions of convex sets, over which linear functions can be optimized efficiently. For the case k = 2 and $\Omega={\cal R}^n$, we present an efficient algorithm for finding tight bounds when S is a union of convex sets, over which convex quadratic functions can be optimized efficiently.
Apply an Augmented Reality in a Mobile Guidance to Increase Sense of Place for Heritage Places

Based on the sense of place theory and the design principles of guidance and interpretation, this study developed an augmented reality mobile guidance system that used a historical geo-context-embedded visiting strategy. This tool for heritage guidance and educational activities enhanced visitor sense of place. This study consisted of 3 visitor groups (i.e., AR-guidance, audio-guidance, and no-guidance) composed of 87 university students. A quasi-experimental design was adopted to evaluate whether augmented reality guidance more effectively promoted sense of place and learning performance than the other groups. The results indicated that visitors who used AR guidance showed significant learning and sense of place effects. Interviews were also employed to determine the possible factors that contribute to the formation of sense of place. Finally, a majority of the visitors who participated in the study demonstrated positive attitudes toward the use of the AR-guidance system.
A study of different weighting schemes for spoken language understanding based on convolutional neural networks

This paper describes the development of a stateless spoken spoken language understanding (SLU) module based on artificial neural networks that is able to deal with the uncertainty of the automatic speech recognition (ASR) output. The work builds upon the concept of weighted neurons introduced by the authors previously and presents a generalized weighting term for such a neuron. The effect of different forms and parameter estimation methods of the weighting term is experimentally evaluated on the multi-task training corpus, created by merging two different semantically annotated corpora. The robustness of the best performing weighting schemes is then demonstrated by experiments involving hybrid word-semantic (WSE) lattices and also limited data scenario.
Effects of Aqueous Extract of Aegle marmelos Root on Chronic Inflammation in Rats

Background: Pain and inflammation is a common complaint in most patients suffering from diseases. Non-steroidal anti-inflammatory drugs (NSAIDs) make up one of the largest groups of drugs used for pain and inflammation but causes side effects during their clinical uses. Therefore, the development of newer more potent anti-inflammatory drugs with lesser side effects is necessary. Aegle marmelos plant has an important place in indigenous systems of medicine. In the study, effect of aqueous extract of Aegle marmelos root on chronic inflammation has been reported. Methods: 24 Norwegian rats of either sex were selected and divided into 4 groups each comprise 6 rats. Chronic inflammation (granuloma) was induced by implanting one autoclaved cotton pellet (50 mg) subcutaneously to one groin of each rat on 1st day. Group II, Group III were given aqueous extract of A. marmelos root at different doses and Group IV were given indomethacin orally for 14 days. Later on the 15 th day animals were anesthetized, the cotton pellets were removed. The dry weight of the granuloma was difference between the final and initial weights of the cotton pellets. The percentage change of granuloma weight relative to control group was taken as an index of chronic anti-inflammatory activity. Results: The percent inhibition of granuloma formation was 8%, 13.72%, and 36.19% as compared to the control in group II, III, IV respectively. Conclusion: In chronic inflammation, Aegle marmelos root possess mild anti-inflammatory effect compared to that of indomethacin.
Factors related to physical activity and recommended intervention strategies as told by midlife and older African American men.

OBJECTIVE Few interventions have targeted preventive health behaviors of midlife and older African American (AA) men. This study derived pertinent information with personal interviews to develop a tailored physical activity (PA) intervention for AA men -45 years of age. METHODS Participants were 49 AA men aged 45-88 years. Personal interviews ascertained PA barriers, enablers, and preferences, and components that would render a PA program appropriate for and appealing to AA men of similar ages. Taped interviews were transcribed and organized in NVivo for analysis. Common themes were identified by multiple research staff. RESULTS Most often cited barriers to PA included time constraints, lack of social support, low motivation, poor access, and factors related to chronic conditions and aging. Although men preferred traditional forms of sports and exercise when younger, they learned to adapt the intensity and duration as they aged, and walking was viewed as an acceptable alternative. Recommended strategies for a community-based PA program were building social support, camaraderie, and accountability among men through healthy/friendly competition and social interaction, using accessible community facilities, and including education about men's and aging-related health issues. CONCLUSION The qualitative research process yielded new and insightful information that can be used to develop a tailored PA and health program for midlife and older AA men.
Individual neural cell types express immunologically distinct N-CAM forms

The neural cell adhesion molecules, or N-CAMs, are a group of structurally and immunologically related glycoproteins found in vertebrate neural tissues. Adult brain N-CAMs have apparent molecular weights of 180,000, 140,000, and 120,000. In this article we identify, using monoclonal antibody (Mab) 3G6.41, an immunologically distinct adult rat N-CAM form and show that this form is selectively expressed by some clonal neural cell lines. Consecutive immunoprecipitation experiments indicate that rabbit anti-N-CAM can remove from solubilized cerebellar neuron primary cultures all 180,000- and 140,000-mol-wt N- CAM molecules that react with Mab 3G6.41. However Mab 3G6.41 cannot remove all N-CAM molecules that react with rabbit anti-N-CAM. Rabbit anti-N-CAM binds to and immunoprecipitates N-CAM forms from the rat neuronal cell lines B35, B65, and B104, the glial lines B12 and C6, and L6 myoblasts. Mab 3G6.41 does not bind to or immunoprecipitate N-CAM from the B12 and B65 lines but does react with the other four lines by both criteria. Many cells in primary cultures of postnatal rat that express glial fibrillary acidic protein also bind Mab 3G6.41. Thus a unique form of rat N-CAM recognized by Mab 3G6.41 is found on some but not all neuronal, glial, and muscle cells.
A low-power RF front-end of passive UHF RFID transponders

This paper presents in details the architecture and most of RF front-end building blocks of a fully integrated passive radio frequency identification (RFID) transponder operating at UHF 902 MHz to 928 MHz. A novel architecture for the transponder IC and a new low power on-off keying (OOK) demodulator are proposed in this paper. For realizing the system, a low power CMOS full-wave rectifier achieving a power conversion efficiency of 31.9% has been integrated in this transponder. Simulation results show that the global input power of front-end circuits is only about 21 muw in order to drive a load of 1.8 muA at the rectifier output and the power consumption of the proposed demodulator is less than 0.4 muw. The transponder is fabricated in a 0.18 mum mixed-mode CMOS technology and has the area of 0.70 mm2.
Incorporating Data Flow Ideas into von Neumann Processors for Parallel Execution

The issues of memory latency, synchronization, and distribution costs in multiprocessors are reviewed. The approaches taken by conventional and data flow architectures are contrasted in relation to these issues. It is pointed out that each approach fits well for a certain situation and that it is possible to have a common framework in which the two execution models can be mixed to suit the situation. An architecture is sketched by describing a few extensions to a conventional processor. While existing programs run without much change, it is shown that improvements could be made by using the new features to tolerate memory latency and to exploit more parallelism. It is shown that data flow graphs can be executed on this to exploit as much parallelism as a data flow architecture could. It is argued that such a testbed will provide for a selective translation of program segments into the appropriate execution model. A fast context switching hardware is presumed for this architecture.
Blood pressure measurements, blood pressure variability and endothelial function in renal transplant recipients

Abstract Background/Aims: Hypertension is an important cardiovascular risk factor in renal transplant recipients. Elevated blood pressure variability (BPV) during 24-h ambulatory blood pressure monitoring (ABPM) is associated with increased risk of target organ damage and cardiovascular events, independent of mean blood pressure levels. We aimed to evaluate the relationship between endothelial function, blood pressure levels obtained by various measurement methods, and BPV in renal transplant recipients. Methods: In total, 73 hypertensive renal transplant recipients were included in the study. Office blood pressure measurements, central blood pressure measurements, home blood pressure measurements and 24-h ABPM were obtained from the subjects. BPV was calculated using the average real variability index. All patients underwent brachial flow-mediated vasodilatation tests. Predictive values of blood pressures obtained by different measurement techniques and BPV on endothelial functions were investigated. Results: Endothelial dysfunction was present in 68.5% of the patients. No difference was found between the group with and without endothelial dysfunction with regard to office systolic or diastolic blood pressure, central blood pressure or home systolic blood pressure. In the group with endothelial dysfunction, 24-h ambulatory systolic blood pressure and night-time ambulatory systolic blood pressure were higher. In patients with endothelial dysfunction, the 24-h systolic, diastolic and mean BPV were all higher. There was also a negative correlation between the percentage of flow-mediated vasodilatation with 24-h mean and systolic BPV. Conclusion: Patients with endothelial dysfunction had significantly higher ambulatory blood pressure values and higher BPV. There was a significant negative correlation between endothelial function and BPV.
Extensive Mitochondrial Heteroplasmy in Natural Populations of a Resurging Human Pest, the Bed Bug (Hemiptera: Cimicidae)

ABSTRACT Homoplasmy, the occurrence of a single mitochondrial DNA haplotype within an individual, has been the accepted condition across most organisms in the animal kingdom. In recent years, a number of exceptions to this rule have been reported, largely due to the ease with which single nucleotide polymorphisms can be detected. Evidence of heteroplasmy—two or more mitochondrial variants within a single individual—has now been documented in a number of invertebrates; however, when present, heteroplasmy usually occurs at low frequencies both within individuals and within populations. The implications of heteroplasmy may be far reaching, both to the individual in relation to its health and fitness, and when considering the evolutionary dynamics of populations.We present novel evidence for frequent mtDNA heteroplasmy in the bed bug, Cimex lectularius L. (Hemiptera: Cimicidae). Our findings show that heteroplasmy is common, with 5 of 29 (17%) populations screened exhibiting two mitochondrial variants in a ∼1:2 ratio within each individual. We hypothesize that the mechanism underlying heteroplasmy in bed bugs is paternal leakage because some haplotypes were shared among unrelated populations and no evidence for nuclear mitochondrial DNA sequences was detected.
Variations in tissue resistivity and in the extension of activated neuron domains shape the voltage signal during spreading depression in the CA1 in vivo

Spreading depression (SD), a wave of neuron activity related to migraine and the ischaemic penumbra, features a moving shell of extracellular negative potential shift (Vo) whose generators are poorly understood. We investigated its subcellular correlates in the hippocampal CA1 in vivo by localizing the neuron domains that generate transmembrane current (Im) using field analysis, and the local changes of tissue resistivity, a major determinant of extracellular current flow. A large increase of tissue resistivity occurred in times and dendritic strata displaying large Vo, albeit with different rates. Typically, SD is composed of basal and apical dendritic components. The apical SD lasts much longer, while it becomes gradually restricted to a narrow dendritic region. Strikingly, pyramidal cells displayed a strong surge of inward current only when SD affected a small dendritic region. However, when the Vo signal covered most of the main neuron axis, only smaller surges of inward current developed at the outer dendritic rims of a wide null current zone. Computational reconstruction showed that this effect was due to strong spatial cancellation of the inward and outward currents in SD‐activated isopotential and shunted regions of individual neurons. Consequently, despite former accounts of large conductance increase, the net Im is small and the large ΔVo amplitude mostly due to increased tissue resistivity. The particular subcellular evolution indicates an initial explosive opening of conductance along most of the pyramidal neuron followed by a wave‐like centripetal closure towards the apical dendrites. The applicability of these mechanisms to SD in other brain regions is discussed.
Leg and Joint Stiffness in Children with Spastic Diplegic Cerebral Palsy during Level Walking

Individual joint deviations are often identified in the analysis of cerebral palsy (CP) gait. However, knowledge is limited as to how these deviations affect the control of the locomotor system as a whole when striving to meet the demands of walking. The current study aimed to bridge the gap by describing the control of the locomotor system in children with diplegic CP in terms of their leg stiffness, both skeletal and muscular components, and associated joint stiffness during gait. Twelve children with spastic diplegia CP and 12 healthy controls walked at a self-selected pace in a gait laboratory while their kinematic and forceplate data were measured and analyzed during loading response, mid-stance, terminal stance and pre-swing. For calculating the leg stiffness, each of the lower limbs was modeled as a non-linear spring, connecting the hip joint center and the corresponding center of pressure, with varying stiffness that was calculated as the slope (gradient) of the axial force vs. the deformation curve. The leg stiffness was further decomposed into skeletal and muscular components considering the alignment of the lower limb. The ankle, knee and hip of the limb were modeled as revolute joints with torsional springs whose stiffness was calculated as the slope of the moment vs. the angle curve of the joint. Independent t-tests were performed for between-group comparisons of all the variables. The CP group significantly decreased the leg stiffness but increased the joint stiffness during stance phase, except during terminal stance where the leg stiffness was increased. They appeared to rely more on muscular contributions to achieve the required leg stiffness, increasing the muscular demands in maintaining the body posture against collapse. Leg stiffness plays a critical role in modulating the kinematics and kinetics of the locomotor system during gait in the diplegic CP.
Consistent Roof Geometry Encoding for 3D Building Model Retrieval Using Airborne LiDAR Point Clouds

A 3D building model retrieval method using airborne LiDAR point clouds as input queries is introduced. Based on the concept of data reuse, available building models in the Internet that have geometric shapes similar to a user-specified point cloud query are retrieved and reused for the purpose of data extraction and building modeling. To retrieve models efficiently, point cloud queries and building models are consistently and compactly encoded by the proposed method. The encoding focuses on the geometries of building roofs, which are the most informative part of a building in airborne LiDAR acquisitions. Spatial histograms of geometric features that describe shapes of building roofs are utilized as shape descriptor, which introduces the properties of shape distinguishability, encoding compactness, rotation invariance, and noise insensitivity. These properties facilitate the feasibility of the proposed approaches for efficient and accurate model retrieval. Analyses on LiDAR data and building model databases and the implementation of web-based retrieval system, which is available at http://pcretrieval.dgl. xyz, demonstrate the feasibility of the proposed method to retrieve polygon models using point clouds.