Miracle-dz/UniFAR-FTUs huggingface dataset:
Long Term Outcomes of Total Hip Arthroplasty in Young Patients under 30.

BACKGROUND We aimed to report outcomes of total hip arthroplasty (THA) in very young patients under the year of 30. METHODS Thirty patients (45 hips) with various indications for THA were retrospectively reviewed radiologically and clinically and analyzed regarding survival, reasons of failure, factors associated with outcomes and postoperative complications. RESULTS Within a mean follow-up time of 116 months the 10-year survival rate was 90.3%. All hips were revised due to aseptic loosening. No association was found among the tested parameters with increased revision rates. Three complications associated with the THA were recorded and managed conservatively. All patients had statistically significant improved clinical scores compared to the pre-operative period, despite the underlying disorder that compromised the condition in the majority of the patients. CONCLUSIONS Our study showed excellent long term outcomes of THA in patients younger than 30 years of age, comparable with those in older patients.
Using Optimization to Obtain a Width-Independent, Parallel, Simpler, and Faster Positive SDP Solver

We study the design of polylogarithmic depth algorithms for approximately solving packing and covering semidefinite programs (or positive SDPs for short). This is a natural SDP generalization of the well-studied positive LP problem. Although positive LPs can be solved in polylogarithmic depth while using only $\tilde{O}(\log^{2} n/\varepsilon^2)$ parallelizable iterations, the best known positive SDP solvers due to Jain and Yao require $O(\log^{14} n /\varepsilon^{13})$ parallelizable iterations. Several alternative solvers have been proposed to reduce the exponents in the number of iterations. However, the correctness of the convergence analyses in these works has been called into question, as they both rely on algebraic monotonicity properties that do not generalize to matrix algebra. In this paper, we propose a very simple algorithm based on the optimization framework proposed for LP solvers. Our algorithm only needs $\tilde{O}(\log^2 n / \varepsilon^2)$ iterations, matching that of the best LP solver. To surmount the obstacles encountered by previous approaches, our analysis requires a new matrix inequality that extends Lieb-Thirring's inequality, and a sign-consistent, randomized variant of the gradient truncation technique proposed in.
Utilization of Resin Infiltration for Prolonging of Tooth Whitening Effects

최근 들어 치아 미백술이 대중화되고 있으나, 단기간내 색소 재침착 등 고유의 한계점이 극복되지는 못 하고 있는 실정이라 할 수 있다. 본 연구는 치아 미백 효과의 색조 안정성을 향상시킬 방법의 하나로서, resin infiltration의 활용 타당성을 평가할 목적으로 시도되었다. 건전한 총 40개 우치 전치 순면으로부터 법랑.
Genome-Wide Analysis of Human MicroRNA Stability

Increasing studies have shown that microRNA (miRNA) stability plays important roles in physiology. However, the global picture of miRNA stability remains largely unknown. Here, we had analyzed genome-wide miRNA stability across 10 diverse cell types using miRNA arrays. We found that miRNA stability shows high dynamics and diversity both within individual cells and across cell types. Strikingly, we observed a negative correlation between miRNA stability and miRNA expression level, which is different from current findings on other biological molecules such as proteins and mRNAs that show positive and not negative correlations between stability and expression level. This finding indicates that miRNA has a distinct action mode, which we called “rapid production, rapid turnover; slow production, slow turnover. ” This mode further suggests that high expression miRNAs normally degrade fast and may endow the cell with special properties that facilitate cellular status-transition. Moreover, we revealed that the stability of miRNAs is affected by cohorts of factors that include miRNA targets, transcription factors, nucleotide content, evolution, associated disease, and environmental factors. Together, our results provided an extensive description of the global landscape, dynamics, and distinct mode of human miRNA stability, which provide help in investigating their functions in physiology and pathophysiology.
Plant regeneration in cotton: A short-term inositol starvation promotes developmental synchrony in somatic embryogenesis

SummaryDespite high commercial interest, the success of biotechnological applications in cotton (Gossypium hirsutum) has been limited due to difficulties in genetic transformation. Major problems have been genotype dependence and low frequency of somatic embryogenesis, making it difficult to regenerate plants from transgenic tissue. This study reports an increase in somatic embryogenesis efficiency and the induction of developmental synchrony in embryogenic callus cultures of cotton by a single cycle of myo-inositol depletion in liquid culture. Calluses were initiated on hypocotyl or cotyledon explants of cultivar Coker 312 by culturing these explants on callus-inducing solid medium [Murashige and Skoog salts plus vitamins of Gamborg's B5 medium, 30 g l−1 glucose, 100 mg l−1myo-inositol, 2.2 μM 2,4-dichlorophenoxyacetic acid, and 0.88 μM 6-benzyladenine]. The calluses were transferred to an identical liquid basal medium devoid of plant growth regulators. This induced the development of embryogenic cells. Friable clumps of cells formed after 20 d in the medium were selectively collected over filter mesh 40 subjected to one cycle of myo-inositol starvation. This induced a highly synchronized embryogenesis in the culture. The optimized protocol gave 100% embryos at the globular stage, out of which more than 80% developed into bipolar torpedo-stage embryos. About 68% of these were converted to plantlets by subculturing onto a simplified solid medium, and finally grown into healthy, fertile plants.
Transcranial Magnetic Stimulation Elicits Coupled Neural and Hemodynamic Consequences

Transcranial magnetic stimulation (TMS) is an increasingly common technique used to selectively modify neural processing. However, application of TMS is limited by uncertainty concerning its physiological effects. We applied TMS to the cat visual cortex and evaluated the neural and hemodynamic consequences. Short TMS pulse trains elicited initial activation (∼1 minute) and prolonged suppression (5 to 10 minutes) of neural responses. Furthermore, TMS disrupted the temporal structure of activity by altering phase relationships between neural signals. Despite the complexity of this response, neural changes were faithfully reflected in hemodynamic signals; quantitative coupling was present over a range of stimulation parameters. These results demonstrate long-lasting neural responses to TMS and support the use of hemodynamic-based neuroimaging to effectively monitor these changes over time.
Oxidative Stress by Visible Light Irradiation Suppresses Immunoglobulin Production in Mouse Spleen Lymphocytes

In this study, we attempted to induce the oxidative stress in mouse spleen lymphocytes with visible light irradiation and examined the effects of lipid peroxidation on immunoglobulin (Ig) production. The spleen lymphocytes were isolated from 8-week-old male balb/c mice and irradiated with 300 W visible light. When the cells were cultured for 72 hr, Ig contents in culture supernatants were decreased gradually by irradiation for over 30 min. The cell viability was also lowered by the irradiation. Intracellular phosphatidylcholine hydroperoxide (PCOOH) levels and thiobarbituric acid-reactive substances (TBARS) values in culture supernatants were measured as indices of lipid peroxidation and we found that Ig production by mouse spleen lymphocytes was suppressed accompanied with the progress of peroxidation of intracellular phospholipids. Cell membrane fluidity was also significantly decreased, but the intracellular Ig level was not changed in the irradiated cells. These results suggest that the peroxidation of intracellular lipids is a cause of the suppression of Ig production by mouse spleen lymphocytes via lowering cell viability and suppressing Ig synthesis and secretion.
Influence of Nomenclature in the Interpretation of Lumbar Disk Contour on MR Imaging: A Comparison of the Agreement Using the Combined Task Force and the Nordic Nomenclatures

There is little agreement between observers when reporting disk abnormalities. These authors evaluated the influence of using criteria set by the Combined Task Force (of which ASNR is a member) and the Nordic Modic Consensus Group Classification in the interpretation of lumbar disk contour. Among the variables assessed on the Nordic form, those analyzed for this study were Schmorl nodes (yes/no) and disk contour (normal, bulging, protrusion [focal or broad-based], and hernia [extrusion or sequestration]). With the CTF form, the recorded variables were intravertebral herniation (yes/no) and disk contour (normal, symmetric bulging disk, focal-based herniation, broad-based herniation, and extrusion). The categorization of intra- and interobserver agreement proved the same across nomenclatures. Intraobserver reliability was substantial for intravertebral herniations and disk contour abnormalities. Interobserver reliability was moderate for intravertebral herniations and fair-to-moderate for disk contour. Conclusions: in clinical practice, regardless of the specific nomenclature used, a standardized nomenclature supports only moderate interobserver agreement. The Nordic nomenclature increases self-confidence in an individual observer's report, but is less clear regarding the classification of disks as normal versus bulging. BACKGROUND AND PURPOSE: The CTF nomenclature had not been tested in clinical practice. The purpose of this study was to compare the reliability and diagnostic confidence in the interpretation of disk contours on lumbar 1.5T MR imaging when using the CTF and the Nordic nomenclatures. MATERIALS AND METHODS: Five general radiologists from 3 hospitals blindly and independently assessed intravertebral herniations (Schmorl node) and disk contours on the lumbar MR imaging of 53 patients with low back pain, on 4 occasions. Measures were taken to minimize the risk of recall bias. The Nordic nomenclature was used for the first 2 assessments, and the CTF nomenclature, in the remaining 2. Radiologists had not previously used either of the 2 nomenclatures. κ statistics were calculated separately for reports deriving from each nomenclature and were categorized as almost perfect (0.81–1.00), substantial (0.61–0.80), moderate (0.41–0.60), fair (0.21–0.40), slight (0.00–0.20), and poor (<0.00). RESULTS: Categorization of intra- and interobserver agreement was the same across nomenclatures. Intraobserver reliability was substantial for intravertebral herniations and disk contour abnormalities. Interobserver reliability was moderate for intravertebral herniations and fair to moderate for disk contour. CONCLUSIONS: In conditions close to clinical practice, regardless of the specific nomenclature used, a standardized nomenclature supports only moderate interobserver agreement. The Nordic nomenclature increases self-confidence in an individual observer's report but is less clear regarding the classification of disks as normal versus bulged.
Local Optimization Based Segmentation of Spatially-Recurring, Multi-Region Objects With Part Configuration Constraints

Incorporating prior knowledge into image segmentation algorithms has proven useful for obtaining more accurate and plausible results. Two important constraints, containment and exclusion of regions, have gained attention in recent years mainly due to their descriptive power. In this paper, we augment the level set framework with the ability to handle these two intuitive geometric relationships, containment and exclusion, along with a distance constraint between boundaries of multi-region objects. Level set's important property of automatically handling topological changes of evolving contours/surfaces enables us to segment spatially-recurring objects (e.g., multiple instances of multi-region cells in a large microscopy image) while satisfying the two aforementioned constraints. In addition, the level set approach gives us a very simple and natural way to compute the distance between contours/surfaces and impose constraints on it. The downside, however, is a local optimization framework in which the final segmentation solution depends on the initialization. In fact, here, we sacrifice the optimizability (local instead of global solution) in exchange for lower space complexity (less memory usage) and faster runtime (especially for large microscopic images) as well as no grid artifacts. Nevertheless, the result from validating our method on several biomedical applications showed the utility and advantages of this augmented level set framework (even with rough initialization that is distant from the desired boundaries). We also compared our framework with its counterpart methods in the discrete domain and reported the pros and cons of each of these methods in terms of metrication error and efficiency in memory usage and runtime.
Minimum makespan workload dissemination in DTNs: making full utilization of computational surplus around

This paper poses the following problem: given a task that originates at some node in a Delay Tolerant Network (DTN), how are we to disseminate the workload during pairwise contacts to minimize the makespan? We first investigate the scenario in which each node has access to an oracle that knows global and future knowledge of node mobility, and we propose a centralized polynomial-time optimal algorithm. We then develop a distributed dissemination protocol, D2, which maintains r-hop neighborhood information at individual nodes. D2 makes dissemination decisions based on the estimations of the potential computational capacities and the future workloads of DTN nodes. Using trace-driven simulations, we show that, D2 with only 1-hop information is already near-optimal in a wide variety of environments, and the performance gap becomes smaller as the amount of information maintained at individual nodes increases.
OPTIMIZING REAL-TIME AUDIO SIGNALS OVER MOBILE NETWORKS

This thesis explores various methods for optimizing real-time audio communications over wireless data networks. Currently, many methods for improving communications deal with optimizing the communications protocol. In this thesis the protocol is not changed, and any protocol is su(cid:14)cient. The methods investigated in this work deal with optimizing communications through signal processing and data manipulation on top of a well-accepted protocol. The optimizations discussed deal with balancing the signal quality, bandwidth, and robustness.
Projection Based Real-Time Material Appearance Manipulation

We introduce a new projection display technique that converts a visual material appearance of target object. Unlike conventional projection display, our approach allowed us successive material appearance manipulation by the projector camera feedback without scene modeling. First, we introduce an appearance control framework with a coaxial projector camera system. Next, we introduce two image based material appearance manipulation methods of translucency and glossiness. Last, we verify the ability of the material appearance manipulation of the proposed display technique through the experiments.
Community and Drug Use among Gay Men

Gay neighborhoods serve as vital places for gay men’s socializing, yet few studies have examined their contributions to gay men’s health—either directly or indirectly via residents’ social networks. Drawing from theoretical perspectives on community and networks, we test hypotheses concerning whether gay neighborhoods and social network factors are associated with patterns of recent illicit drug use among a sample of 740 urban gay men from New York City. Higher odds of drug use were observed among individuals who resided in gay neighborhoods, had networks composed predominantly of other gay men, and had increased socialization with gay men. Network factors did not mediate associations between gay neighborhoods and drug use. These findings highlight the need to better contextualize the health risks faced by gay men by accounting for both neighborhood and network structures.
On localization and mapping with RGB-D sensor and hexapod walking robot in rough terrains

In this paper, we address a problem of precise online localization of a hexapod walking robot operating in rough terrains. We consider an existing Simultaneous Localization and Mapping approach with a low cost structured light (RGB-D) sensor. We propose to combine this sensor and localization method with the developed adaptive motion gait that allows the robot to crawl various types of terrain, such as stairs, ramps, or small wooden blocks. Such an environment requires a full 6-DOF pose estimation to create a map of the robot surroundings and allows us to asses impact of the individual terrain types and influence of the SLAM method parametrization on the localization accuracy. The reported evaluation results indicate the relations between the terrain type, parametrization of the method and the localization accuracy.
In Vivo Characterization of the Pharmacodynamics of Flucytosine in a Neutropenic Murine Disseminated Candidiasis Model

ABSTRACT In vivo pharmacodynamic parameters have been characterized for a variety of antibacterial agents. These parameters have been studied in correlation with in vivo outcomes in order to determine (i) which dosing parameter is predictive of outcome and (ii) the magnitude of that parameter associated with efficacy. Very little is known of the pharmacodynamics of antifungal agents. We used a neutropenic murine model of disseminated candidiasis to correlate the pharmacodynamic parameters (percentage of time above the MIC, area under the concentration-time curve [AUC]/MIC and peak level/MIC) for flucytosine (5-FC) in vivo with efficacy as measured by organism number in homogenized kidney cultures after 24 h of therapy. The pharmacokinetics of 5-FC in infected mice were linear. Serum half-lives ranged from 0.36 to 0.43 h. Infection was achieved by intravenous inoculation of 106 CFU of yeast cells per ml via the lateral tail vein of neutropenic mice. Groups of mice were treated with fourfold escalating total doses of 5-FC ranging from 1.56 to 400 mg/kg of body weight/day divided into one, two, four, or eight doses over 24 h. Increasing doses produced minimal concentration-dependent killing ranging from 0 to 0.9 log10 CFU/kidneys. 5-FC did, however, produce a dose-dependent suppression of growth after levels in serum had fallen below the MIC. The fungistatic dose increased from 6 to 8 mg/kg with dosing every 3 and 6 h to 70 mg/kg at with dosing every 24 h. Nonlinear regression analysis was used to determine which pharmacodynamic parameter best correlated with efficacy. Time above the MIC was the parameter best predictive of outcome, while AUC/MIC was only slightly less predictive (time above MIC,R2 = 85%; AUC/MIC,R2 = 77%; peak level/MIC,R2 = 53%). Maximal efficacy was observed when levels exceeded the MIC for only 20 to 25% of the dosing interval. If one considers drug kinetics in humans, these results suggest reevaluation of current dosing regimens.
Improving the Convergence of RTDP

Real-time dynamic programming (RTDP) is an outstanding real-time algorithm for solving non-deterministic planning problems with full observability. RTDP has two key advantages comparing with other DP algorithms: first, it obtain an optimal policy without computing the whole space, second, it has a good anytime behavior. However, RTDP's convergence is slow. In this paper, we introduce RTDP(k), an algorithm based on RTDP with a similar structure. RTDP(k) improves the convergence as well as holds real-time algorithm properties. RTDP(k) updates k extended states per iteration following a "bounded propagation strategy". In Markov decision processes (MDPs), especially in stochastic shortest-path problems (SSPs), we have proved two points: first, every RTDP(k) trial terminates in a finite number of steps ,second, RTDP(k) eventually converges to an optimal policy. From a practical point of view, We show that RTDP(k) produces better solutions in the first trial and converges faster than RTDP on benchmarks for real-time search.
Monte Carlo set-membership filtering for nonlinear dynamic systems

When underlying probability density functions of nonlinear dynamic systems are unknown, the filtering problem is known to be a challenging problem. This paper attempts to make progress on this problem by proposing a new class of filtering methods in bounded noise setting via set-membership theory and Monte Carlo (boundary) sampling technique, called Monte Carlo set-membership filter. The set-membership prediction and measurement update are derived by recent convex optimization methods based on S-procedure and Schur complement. To guarantee the on-line usage, the nonlinear dynamics are linearized about the current estimate and the remainder terms are then bounded by an optimization ellipsoid, which can be described as a semi-infinite optimization problem. In general, it is an analytically intractable problem when dynamic systems are nonlinear. However, for a typical nonlinear dynamic system in target tracking, we can analytically derive some regular properties for the remainder. Moreover, based on the remainder properties and the inverse function theorem, the semi-infinite optimization problem can be efficiently solved by Monte Carlo boundary sampling technique. Compared with the particle filter, numerical examples show that when the probability density functions of noises are unknown, the performance of the Monte Carlo set-membership filter is better than that of the particle filter.
The Optoelectronic Property of Single CdSe Nanowire/monolayer Graphene Heterojunctions

Here, graphene have been synthesized via a simple chemical vapor deposition method on Cu chip [6] , and then transferred to a clean silicon substrate with 300nm oxide layer. The CdSe nanowires have also been synthesized via a simple chemical vapor deposition method at 0.5Mpa in a horizontal quartz tube furnace [7] . After the electrodes on graphene were done, the CdSe nanowire was transferred from silicon substrate to across on the graphene directly by glass fiber under an optical microscope.
Multiple traveling salesman problem using novel crossover and group theory

This paper propose a new technique which uses novel crossover with multi chromosome representation using group theory for tour construction for solving the multiple traveling salesmen problem (MTSP) using a genetic algorithm (GA) for near-optimal solutions. In the proposed algorithm, we use group tour construction method to get population having rich diversity. In group tour construction method each individual / initial tour is distinct provided that population size is less than the total number of cities. We also use multi chromosome representation technique, which minimizes the search space. We evaluated and compare the proposed technique with four different crossover methods for two MTSP objective functions, namely, total travel of the cost of m tours of the m salesman and longest tour cost travel by any one salesman. In this MTSP, we minimize these objective functions. Computational results obtained from proposed crossover with group tour construction is better than T CX, ORX+A, CYX+A, PMX + A crossover based method.