Miracle-dz/UniFAR-FTUs huggingface dataset:
Improving Few-Shot Visual Classification with Unlabelled Examples

We propose a transductive meta-learning method that uses unlabelled instances to improve few-shot image classification performance. Our approach combines a regularized Mahalanobis-distance-based soft k-means clustering procedure with a modified state of the art neural adaptive feature extractor to achieve improved test-time classification accuracy using unlabelled data. We evaluate our method on transductive few-shot learning tasks, in which the goal is to jointly predict labels for query (test) examples given a set of support (training) examples. We achieve new state of the art performance on Meta-Dataset, and produce competitive results on mini- and tiered-ImageNet benchmarks.
Harmonic Optimization of Multilevel Inverter

-In present work, optimization techniques genetic algorithm (GA) and particle swarm optimization (PSO) are used to compute switching angles for the cascaded multilevel inverter for selective harmonic elimination and the results are compared. Switching angles obtained from PSO produced better output with less harmonic content. Due to better performance PSO results are used further to obtain training set for Artificial Neural Network (ANN). Hence implementation of ANN for the elimination of low order harmonics is presented. Output voltage for nine level inverter is obtained for both single phase and three phase Cascaded Multilevel Inverter (CMLI). Switching angles are calculated through GA and PSO for various modulation indices and for minimum Total Harmonic Distortion (THD). Simulation results are presented using MATLAB and m file program. Through ANN real time implementation is possible with significantly reduced lower harmonics and improved performance.
Use of Video-Assisted Thoracoscopic Surgery to Reduce Perioperative Morbidity in Scoliosis Surgery

Study Design. A case series of idiopathic scoliosis patients treated with thoracoscopic anterior instrumentation was compared to a similar group of patients treated by open anterior instrumentation. Objectives. To evaluate the morbidity associated with thoracoscopic instrumentation compared to the open approach for thoracic scoliosis. Methods. A consecutive group of thoracoscopically treated patients with Lenke 1 adolescent idiopathic scoliosis was compared to similar patients gathered from the DePuy-AcroMed Harms Study Group database. Perioperative outcome measures as well as early postoperative functional outcomes (pulmonary function, shoulder strength) were compared. Results. There were 38 thoracoscopic instrumentation cases with greater than 6 months’ follow-up that were compared to 68 anterior open instrumentation cases. The radiographic outcomes were similar (60% ± 11%vs. 59% ± 17% thoracic curve correction for the thoracoscopic and open groups, respectively). The reduction in forced vital capacity was significantly (P = 0.01) greater in the open group (0.6 ± 0.3 L) compared to the endoscopic group (0.4 ± 0.3 L). There was a trend towards greater return of shoulder girdle strength and range of motion 6 weeks after surgery in the thoracoscopic patients. Conclusion. The thoracoscopic approach for instrumentation of scoliosis has advantages of reduced chest wall morbidity compared with the open thoracotomy method but allows comparable curve correction.
Multifocal visual evoked potential latency analysis: predicting progression to multiple sclerosis.

OBJECTIVE To monitor the difference in conversion rates to multiple sclerosis (MS) in 46 patients with optic neuritis between patients with multifocal visual evoked potential latency delay and those with normal latency. DESIGN Prospective case series. SETTING Metropolitan neuro-ophthalmology clinic. PARTICIPANTS Forty-six patients with optic neuritis who did not have a diagnosis of MS on enrollment in the study. MAIN OUTCOME MEASURES Conversion to MS according to the McDonald criteria. RESULTS Analysis revealed that only 22 subjects had multifocal visual evoked potential latency delay. Over 1 year, 36.4% of patients with optic neuritis with latency delays progressed clinically to MS compared with 0% of those with normal latencies (P = .03, chi2). CONCLUSION This may indicate that multifocal visual evoked potential latency delay can assist in predicting progression to future MS.
Managerial Characteristics and Hedge Fund Performance

The tremendous growth in assets managed in hedge funds is well recognized. However, monitoring, valuation and performance assessment is confounded by the paucity and inconsistency of available data. Hedge funds do not regularly report their performance and rarely divulge holdings. Utilizing a unique data set we are able to shed some light on the relationship between performance and various hedge fund manager characteristics. We examine the influence of characteristics such as education and prior work experience on performance by hedge fund style for 147 hedge funds over the 1994-2004 period. Our results indicate that managers with degrees from top US schools outperform their peers unless those degrees are in economics or technical fields. Managers with undergraduate degrees in economics and especially those from top ranked schools significantly underperform their peers and the same result occurs, but less significantly, with technical degrees. Prior work experience does not change these results and they are also robust to the type of strategy employed by the hedge fund and alternative measures of performance including the Stutzer Index and Omega Measure. Thus, our results have interesting implications for the selection of hedge fund managers and particularly for the formation of diversified asset class targeted hedge fund products such as funds of funds.
Adaptive minimum variance coupled with sign and phase coherence factors in IQ domain for plane wave beamforming

In the framework of PICMUS challenge, the objective comparison between steered plane waves beamforming is proposed on an external platform. Our beamforming proposal consists in a weighted minimum variance approach which combines a phase coherence factor calculation and a minimum variance beamforming. The computation is made in the IQ domain in order to reduce the calculation effort. An adaptive scheme is used to optimize the number of elements that are considered for the MV beamforming, which depends on the depth and the lateral position of the reconstructed pixel. Moreover, the coherence maps are filtered in order to avoid strong discontinuities and speckle penalty on the platform. The obtained results on the MIDAS platform demonstrates higher CNR and resolution compare to classical DAS approach. The main limitation of our weighted MV lies on the final axial resolution which is not improved and limits the overall performance of the method.
Learning and memory in combat veterans with posttraumatic stress disorder.

OBJECTIVE The authors investigated a broad range of memory functions for stimuli unrelated to trauma to determine whether symptoms such as intrusive memories might reflect an underlying cognitive deficit unrelated to the psychological content of the traumatic memory in patients with posttraumatic stress disorder (PTSD). METHOD The authors measured the intellectual functioning of 20 male combat veterans with PTSD and 12 normal comparison subjects using the WAIS and evaluated them for performance on memory using the California Verbal Learning Test. RESULTS Veterans with PTSD showed normal abilities in the functions of initial attention, immediate memory, cumulative learning, and active interference from previous learning. However, these veterans showed a circumscribed cognitive deficit, manifested by the presence of substantial retroactive interference and revealed by a significant decrement in retention following exposure to an intervening word list. CONCLUSIONS The data suggest that patients with PTSD may have fairly specific deficits in the monitoring and regulation of memory information.
Lysyl Oxidase Expression Is Decreased in the Developing Diaphragm and Lungs of Nitrofen-Induced Congenital Diaphragmatic Hernia

Abstract Introduction Malformation of the nonmuscular tissue components in congenital diaphragmatic hernia (CDH) is thought to underlie the diaphragmatic defect, causing intrathoracic herniation of abdominal viscera and thus disturbing normal lung development. It has been shown that diaphragmatic and pulmonary morphogeneses require the structural integrity of connective tissue, and developmental mutations that inhibit the formation of extracellular matrix (ECM) result in CDH with hypoplastic lungs. Lysyl oxidase (lox), an extracellular enzyme that catalyzes the cross-linking of ECM proteins, plays an essential role during diaphragmatic and pulmonary development by controlling the formation of connective tissue. Furthermore, lox −/− knockouts exhibit abnormal connective tissue with diaphragmatic defects and impaired airway morphogenesis. We designed this study to investigate the hypothesis that diaphragmatic and pulmonary lox expression is decreased in the nitrofen-induced CDH model. Materials and Methods Timed-pregnant Sprague-Dawley rats were exposed to either nitrofen or vehicle on gestational day 9 (D9), and fetuses were harvested on selected time points D15 and D18. The micro-dissected fetal diaphragms (n = 48) and lungs (n = 48) were divided into two groups: control and nitrofen-exposed samples (n = 12 per specimen and time point, respectively). Diaphragmatic and pulmonary gene expression levels of lox were analyzed by quantitative real-time polymerase chain reaction. Immunohistochemical staining was performed to evaluate lox protein expression in diaphragms and lungs. Results Relative mRNA expression of lox was significantly reduced in diaphragms and lungs of nitrofen-exposed fetuses on D15 (0.29 ± 0.08 vs. 0.12 ± 0.05; p < 0.05 and 0.52 ± 0.44 vs. 0.20 ± 0.04; p < 0.05) and D18 (0.90 ± 0.25 vs. 0.57 ± 0.23; p < 0.05 and 0.59 ± 0.26 vs. 0.35 ± 0.09; p < 0.05) compared with controls. Diaphragmatic and pulmonary immunoreactivity of lox was markedly decreased in nitrofen-exposed fetuses on D15 and D18 compared with controls. Conclusions Decreased lox expression during diaphragmatic development and lung branching morphogenesis may interfere with normal cross-linking of ECM proteins, disrupting the integrity of connective tissue, and contributing to the diaphragmatic defect and impaired airway formation in the nitrofen-induced CDH model.
Elemental distribution in Rana pipiens retinal rods: quantitative electron probe analysis.

The composition of dark‐adapted and illuminated retinal rod outer and inner segments and mitochondria was determined with electron probe X‐ray micro‐analysis of cryosections. The concentration of Ca in the outer segment was 0.4 mmol/kg dry wt. (0.1 Ca/rhodopsin) and did not measurably change upon illumination with saturating light for 5 min. The non‐mitochondrial regions of the inner segment contained the highest concentrations (up to 13 mmol/kg dry wt.) of Ca in rods; these regions probably represent the endoplasmic reticulum. The equilibrium potentials estimated from the measured elemental concentrations and the known water content of dark‐adapted outer segments were (mV): ENa = +17, EK = ‐83, ECl = ‐27. The respective values in the inner segment were: ENa = +20, EK = ‐89, ECl = ‐26. The above values were obtained in frog rods bathed in 0.18 mM‐Ca Ringer solution. In the outer segment of toad rods bathed in 1.8 mM‐Ca Ringer, ENa = +33 mV. The Mg content of the rods was high. The (computed) concentration in the dark‐adapted retinae was 11 mM in the outer segment and 24 mM in the inner segment. Illumination caused a reduction in Mg to 9 mM (outer segment) and 16 mM (inner segment). Illumination caused a highly significant reduction in Na and Cl concentrations, and an increase in K concentration in both outer and inner segments. Exposure to Na‐free (choline Ringer) solution resulted in reduction in Na to just‐detectable levels (3 +/‐ 1 mmol/kg dry wt.) in the outer segment and to 5 +/‐ 1 mM in the inner segment. This was associated with a significant loss of Cl and decrease in ECl to ‐50 mV. The low Na content of the outer segment in the Na‐depleted rods is not compatible with an extracellular concentration (105 mM) of inexchangeable Na in the intradiskal space. Mitochondrial Na and Mg paralleled the changes in the cytoplasmic concentrations: both mitochondrial Na and Mg were significantly decreased in illuminated, compared to dark‐adapted rods. There was no detectable Ca (0 +/‐ 0.2 mmol/kg dry wt.) in mitochondria of dark‐adapted rods containing high concentrations of Na; mitochondrial Ca was slightly higher (0.5 +/‐ 0.2 mmol/kg dry wt.) in the mitochondria that contained low Na following illumination.
Sketched Newton-Raphson

We propose a new globally convergent stochastic second order method. Our starting point is the development of a new Sketched Newton-Raphson (SNR) method for solving large scale nonlinear equations of the form $F(x)=0$ with $F: \mathbb{R}^d \rightarrow \mathbb{R}^d$. We then show how to design several stochastic second order optimization methods by re-writing the optimization problem of interest as a system of nonlinear equations and applying SNR. For instance, by applying SNR to find a stationary point of a generalized linear model (GLM), we derive completely new and scalable stochastic second order methods. We show that the resulting method is very competitive as compared to state-of-the-art variance reduced methods. Using a variable splitting trick, we also show that the Stochastic Newton method (SNM) is a special case of SNR, and use this connection to establish the first global convergence theory of SNM. Indeed, by showing that SNR can be interpreted as a variant of the stochastic gradient descent (SGD) method we are able to leverage proof techniques of SGD and establish a global convergence theory and rates of convergence for SNR. As a special case, our theory also provides a new global convergence theory for the original Newton-Raphson method under strictly weaker assumptions as compared to what is commonly used for global convergence. There are many ways to re-write an optimization problem as nonlinear equations. Each re-write would lead to a distinct method when using SNR. As such, we believe that SNR and its global convergence theory will open the way to designing and analysing a host of new stochastic second order methods.
Learning compact generalizable neural representations supporting perceptual grouping

Work at the intersection of vision science and deep learning is starting to explore the efficacy of deep convolutional networks (DCNs) and recurrent networks in solving perceptual grouping problems that underlie primate visual recognition and segmentation. Here, we extend this line of work to investigate the compactness and generalizability of DCN solutions to learning low-level perceptual grouping routines involving contour integration. We introduce V1Net, a bio-inspired recurrent unit that incorporates lateral connections ubiquitous in cortical circuitry. Feedforward convolutional layers in DCNs can be substituted with V1Net modules to enhance their contextual visual processing support for perceptual grouping. We compare the learning efficiency and accuracy of V1Net-DCNs to that of 14 carefully selected feedforward and recurrent neural architectures (including state-of-the-art DCNs) on MarkedLong -- a synthetic forced-choice contour integration dataset of 800,000 images we introduce here -- and the previously published Pathfinder contour integration benchmarks. We gauged solution generalizability by measuring the transfer learning performance of our candidate models trained on MarkedLong that were fine-tuned to learn PathFinder. Our results demonstrate that a compact 3-layer V1Net-DCN matches or outperforms the test accuracy and sample efficiency of all tested comparison models which contain between 5x and 1000x more trainable parameters; we also note that V1Net-DCN learns the most compact generalizable solution to MarkedLong. A visualization of the temporal dynamics of a V1Net-DCN elucidates its usage of interpretable grouping computations to solve MarkedLong. The compact and rich representations of V1Net-DCN also make it a promising candidate to build on-device machine vision algorithms as well as help better understand biological cortical circuitry.
The cardiovascular effects of insulin

Introduction: Cardiovascular disease remains one of the leading causes of morbidity and mortality in diabetes mellitus. A causal link between insulin, atherosclerosis and cardiovascular risk has been investigated at the basic science level and studied in large clinical trials. Areas covered: The cardiovascular actions of insulin and its role at the level of the endothelium will be reviewed. Cardiovascular outcomes in several large diabetes trials where insulin management was prominent will be summarized. Expert opinion: The vascular actions of insulin are complex and mediated primarily via nitric oxide and endothelin-1. It appears that insulin resistance, rather than hyperinsulinemia itself, increases cardiovascular risk. In fact, hyperinsulinemia in the setting of normal beta cell function protects obese and insulin-resistant individuals from type 2 diabetes. Large clinical trials have supported that insulin management is not associated with increased adverse outcomes. A multifactorial approach targeting modifiable risk factors, including smoking cessation, blood pressure and lipid management, reduces cardiovascular risk. Therapy goals should be individualized and hypoglycemia, especially in individuals receiving insulin management, should be strictly avoided.
Effect of Dialysate Temperature and Diabetes on Autonomic Cardiovascular Regulation during Hemodialysis

Background/Aims: Lowering dialysate temperature to increase intradialytic hemodynamic stability may interfere with the ultrafiltration-dependent intradialytic autonomic cardiovascular regulation. The present study aimed to investigate hemodynamic and autonomic responses depending on dialysate temperature and the presence of diabetes. Methods: Seventeen (8 diabetic, 9 non-diabetic) hypotension-resistant patients were alternately treated at dialysate temperatures of 37 and 35°C. Hemodynamic parameters, heart rate variability (HRV) and baroreceptor reflex sensitivity (BRRS) were measured noninvasively. Power spectral analysis of HRV was used to evaluate cardiac sympathetic and parasympathetic activity. Results: In contrast to diabetic patients who showed an overall reduced autonomic activity and a blunted autonomic response, in non-diabetic patients cardiac sympathetic activity increased during dialysis (p < 0.05) resulting in a shift in sympathovagal balance towards sympathetic predominance. This response was not altered by dialysate temperature. Significant decreases in stroke volume and cardiac output were found in both patient groups. Total peripheral resistance increased in diabetic (p < 0.05) and in non-diabetic patients (p < 0.01) at both dialysate temperatures. No differences in BRRS were determined. Conclusion: The presence of diabetes has great impact on the cardiovascular autonomic regulation during hemodialysis. Varying the dialysate temperature does not influence cardiovascular autonomic regulation in hemodynamically stable diabetic and non-diabetic patients.
Approximate feasibility in real-time scheduling : Speeding up in order to meet deadlines

In real-time scheduling, feasibility analysis aims at determining whether a task system that emits jobs at regular time intervals, is schedulable on a given set of resources such that all deadlines can be met. Computational hardness and uncertainty obstruct determining feasibility exactly. Therefore performance of approximate feasibility testing and scheduling algorithms for a given processor environment is measured by the speedup factor; the extra speed the processor(s) require to schedule a task system with such an algorithm, given that the task system is feasible if processor(s) run at unit speed. In this dissertation, feasibility tests and scheduling algorithms are given for various problem settings from real-time scheduling. Upper and lower bounds on the required speedup factors are shown.
Angel investing : matching start-up funds with start-up companies : the guide for entrepreneurs, individual investors, and venture capitalists

FINANCING OPTIONS FOR START--UP FIRMS. Funding Entrepreneurial Firms. Bootstrapping Internally and the Challenges to Securing Outside Finance. Types of Outside Investors Willing to Finance Growing Firms. THE TWO MAIN SOURCES OF FUNDING: BUSINESS ANGELS AND VENTURE CAPITALISTS. The Value of Business Angels and Venture Capitalists. Harnessing the Power of Business Angels and Venture Capitalist. Understanding the Investors' Structural and Personal Differences. BUSINESS ANGEL AND VENTURE CAPITALIST DIFFERENCES THROUGHOUT THE INVESTMENT PROCESS. Investors' Motivations and Investment Criteria. Screening the Deal and Conducting Due Diligence. Negotiating and Forming the Legal Contract. Monitoring the Investment. Exiting the Investment and Realizing Returns. ATTRACTING BUSINESS ANGEL FUNDS TO YOUR START--UP FIRM. Valuing Your Firm. Negotiating the Funding Agreement. BECOMING A SUCCESSFUL BUSINESS ANGEL INVESTOR. Steps in Effectively Making Your First Investment in an Entrepreneurial Firm. THE FUTURE OF THE BUSINESS ANGEL MARKET. The Business Angel Market in the New Millennium. PUTTING THE WHEELS INTO MOTION. Appenxix 1: A Detailed List of More than Seventy Matching Services in the United States. Appendix 2: Further Helpful Resourses. Appendix 3: Writing a Winning Business Plan. Glossary. Bibliography. Name Index. Subject Index.
Journal of Internet Banking and Commerce an Empirical Investigation of the Level of Users' Acceptance of E-banking in Nigeria Aderonke a Adesina Holds a B.sc and M.sc. Degree in Management Information

Nigeria was depicted to be the fastest growing telecommunications nation in African. Presently, all members of the Nigeria banking industry have engaged the use of Information and Communication Technology (ICT) as a platform for effective and efficient means of conducting financial transactions. This paper focuses on determining the level of users' acceptance of the electronic banking services and investigating the factors that determine users' behavioral intentions to use electronic banking systems in Nigeria. The survey instrument employed involved design and administration of a total of 500 survey questionnaires within the Lagos metropolis and its environs. An extended Technology Acceptance Model (TAM) was employed as a conceptual framework to investigate the factors that influence users' acceptance and intention to use electronic banking. To test the model, data was collected from 292 customers from various commercial banks in Nigeria. The model measured the impact of Perceived Credibility (PC), Computer Self-Efficacy (CSE), Perceived Usefulness (PU), and Perceived Ease of Use (PEOU) on customer attitude and customer attitude on customer adaptation. The result of this research shows that ATM still remains the most widely used form e-Banking service. Banks' customers who are active users of e-Banking system use it because it is convenient, easy to use, time saving and appropriate for their transaction needs. Also the network security and the security of the system in terms of privacy are the major concerns of the users and constitute hindrance to intending users.