Standard Reduction Techniques Research Articles

Using machine learning for efficient flexible regression adjustment in economic experiments

This study investigates the optimal use of covariates in reducing variance when analyzing experimental data. We show that finding the variance-minimizing strategy for making use of pre-treatment observables is equivalent to estimating the conditional expectation function of the outcome given all available pre-randomization observables. This is a pure prediction problem, which recent advances in machine learning (ML) are well-suited to tackling. Through a number of empirical examples, we show how ML-based regression adjustments can feasibly be implemented in practical settings. We compare our proposed estimator to other standard variance reduction techniques in the literature. Two important advantages of our ML-based regression adjustment estimator are that (i) they improve asymptotic efficiency relative to other alternatives and (i i) they can be implemented automatically, with relatively little tuning from the researcher, which limits the scope for data-snooping.

Cauchy robust principal component analysis with applications to high-dimensional data sets

Principal component analysis (PCA) is a standard dimensionality reduction technique used in various research and applied fields. From an algorithmic point of view, classical PCA can be formulated in terms of operations on a multivariate Gaussian likelihood. As a consequence of the implied Gaussian formulation, the principal components are not robust to outliers. In this paper, we propose a modified formulation, based on the use of a multivariate Cauchy likelihood instead of the Gaussian likelihood, which has the effect of robustifying the principal components. We present an algorithm to compute these robustified principal components. We additionally derive the relevant influence function of the first component and examine its theoretical properties. Simulation experiments on high-dimensional datasets demonstrate that the estimated principal components based on the Cauchy likelihood typically outperform, or are on a par with, existing robust PCA techniques. Moreover, the Cauchy PCA algorithm we have used has much lower computational cost in very high dimensional settings than the other public domain robust PCA methods we consider.

PSR J1910–5959A: A rare gravitational laboratory for testing white dwarf models

Context. PSR J1910−5959A is a binary millisecond pulsar in a 0.837 day circular orbit around a helium white dwarf (HeWD) companion. The position of this pulsar is 6.3 arcmin (∼74 core radii) away from the optical centre of the globular cluster (GC) NGC 6752. Given the large offset, the association of the pulsar with the GC has been debated. Aims. We aim to obtain precise measurements of the masses of the stars in the system along with secular orbital parameters, which will help identify if the system belongs to the GC. Methods. We have made use of archival Parkes 64 m ‘Murriyang’ telescope data and carried out observations with the MeerKAT telescope with different backends and receivers over the last two decades. Pulse times of arrival were obtained from these using standard pulsar data reduction techniques and analysed using state-of-the-art Bayesian pulsar timing techniques. We also performed an analysis of the pulsar’s total intensity and polarisation profile to understand the interstellar scattering along the line of sight, and we determined the pulsar’s geometry by fitting the rotating vector model to the polarisation data. Results. We obtain precise measurements of several post-Keplerian parameters: the range, r = 0.202(6) T⊙, and shape, s = 0.999823(4), of the Shapiro delay, from which we infer: the orbital inclination to be 88.9−0.14+0.15 deg; the masses of the pulsar and the companion to be 1.55(7) M⊙ and 0.202(6) M⊙, respectively; a secular change in the orbital period Ṗb = −53−6.0+7.4 × 10−15 s s−1 that proves the GC association; and a secular change in the projected semi-major axis of the pulsar, ẋ = −40.7−8.2+7.3 × 10−16 s s−1, likely caused by the spin–orbit interaction from a misaligned HeWD spin, at odds with the likely isolated binary evolution of the system. We also discuss some theoretical models for the structure and evolution of white dwarfs in neutron star–white dwarf binaries, using PSR J1910−5959A’s companion as a test bed. Conclusions. PSR J1910−5959A is a rare system for which several parameters of both the pulsar and the HeWD companion can be accurately measured. As such, it is a test bed for discriminating between alternative models of HeWD structure and cooling.

Efficient Point-to-Point Resistance Distance Queries in Large Graphs

We describe a method to efficiently compute point-to-point resistance distances in a graph, which are notoriously difficult to compute from the raw graph data. Our method is based on a relatively compact hierarchical data structure which ''compresses'' the resistance distance data present in a graph, constructed by a nested bisection of the graph using compact edge-cuts. Built and stored in a preprocessing step (which is amenable to massive parallel processing), efficient traversal of a small portion of this data structure supports efficient and exact answers to resistance distance queries. The size of the resulting data structure for a graph of $n$ vertices is $O(nk\log n)$, where $k$ is the size of a balanced edge-cut of the graph. Exact queries then require $O(k\log n)$ worst-case time and $O(k)$ average-case time. Approximate values may be obtained significantly faster by applying standard dimension reduction techniques to the ''coordinates'' stored in the structure.

Deep autoencoder based hybrid dimensionality reduction approach for classification of SERS for melanoma cancer diagnostics

Melanoma, a kind of fatal skin cancer, originates in melanin secreting cells of the dermis. Disease identification in the early stages assures a high survival rate for the patient. Most of the existing techniques retard the cancer detection phase. Surface-Enhanced Raman Spectroscopy (SERS) can capture fine details from the specimens that machine learning models can utilize to discriminate between healthy and diseased individuals rapidly. Our research work proposes a deep autoencoder based hybrid dimensionality reduction approach with a machine learning model on SERS spectrums of human skin fibroblast for melanoma cancer diagnostics. SERS measurements of 307 samples in total, belonging to two different classes, such as normal (157 samples) and malignant melanoma (150 samples), are used in this study. The SERS spectra measurements for both the samples lie between 100cm-1 and 4278cm-1. The variations in the intensity of Raman bands between both classes are intrinsically subtle. Neighborhood Component Analysis (NCA) technique has been exerted to transform 2090 dimensional spectral features into 2090 dimensional vectors and then the Deep Autoencoder (DAE) model is used to handle the nonlinearity in the data and produce the latent space, while Linear Discriminant Analysis (LDA) classifier have been employed for discriminating the normal and cancer cells. The k-fold cross-validation technique with a k value of 10 is implemented to assess the metrics of the model. The stated hybrid (NCA and DAE) model with 10-dimension latent space achieves an accuracy of 98%, the sensitivity of 99% and specificity of 97%, respectively. Due to the high-intensity nature of the SERS spectrum, the existing linear dimensionality reduction based discriminating model fails if the class label (Normal or Cancer) gets distributed on the low variance side. The proposed methodology captures both linear and nonlinear underlying structures present in the spectrums, resulting in better classification compared to the standard dimensionality reduction techniques.

Antegrade Intramedullary Fixation for Clavicular Shaft Fracture: A Technical Trick.

The standard open reduction and internal fixation technique with a plate and screws for a simple mid shaft clavicular fracture necessitates a relatively large incision and can also lead to variable amount of keloid scar formation. Historically, other techniques of more minimally invasive retrograde intramedullary fixation with the entry point posterolaterally on the shoulder have shown their own disadvantages and complications. We present a surgical technique of antegrade intramedullary fixation for mid shaft clavicular fractures and an illustrative case series.

Treatment of Complex Hindfoot Trauma with Hindfoot Nail

Category:Hindfoot; TraumaIntroduction/Purpose:Pilon fractures are often associated with severe bone comminution and soft tissue compromise. As a result, surgical salvage procedures such as hindfoot nailing may be indicated for patients who are not candidates for standard fixation techniques such as open reduction and internal fixation (ORIF). The purpose of this review was to access outcomes associated with complex hindfoot trauma acutely treated with hindfoot nailing.Methods:A case series at a Level I trauma center was performed to identify trauma patients with complex hindfoot fractures who underwent hindfoot nailing as definitive treatment after initial external fixation between 2012 and 2020. Indications included a combination of patient comorbidities, fracture severity, and soft tissue injury. Exclusion criteria included follow-up less than 3 months. Post-operative radiographs were interpreted by a fellowship-trained foot and ankle surgeon. Primary outcome measures included unplanned reoperation/revision and deep infection. Deep infection was defined as any patient requiring surgical debridement after definitive fixation with positive cultures or the presence of positive cultures at the time of planned surgery. Fractures were classified using the AO/OTA classification and injury characteristics and postoperative complications were recorded via chart review.Results:Twenty-six of 29 of identified patients met inclusion criteria. The most common AO/OTA classification was 43C (62%). The average age was 55 years (range, 31-94) and the most common mechanism of injury was motor vehicle crash (38%). Thirteen fractures (50%) were open with Gustilo Anderson grade IIIA fractures being the most common (38%). The overall deep infection rate was 15% with fifty percent of cases positive for a history of diabetes mellitus or smoking. Unplanned reoperations occurred in seven (27%) cases. Among these, a total of four (57%) occurred due to the development of deep infection, two (29%) were nonunions, and one (14%) was indicated for hardware failure. Below the knee amputation occurred in one patient with nonunion (4%), which was a grade IIIA open pilon fracture with significant bone loss. Union was achieved in the majority of patients (92%).Conclusion:Treatment of complex hindfoot trauma with intramedullary nailing has a high union rate as a salvage procedure in a poor host. Surgeons should consider this treatment in patients that are not candidates for standard open reduction and internal fixation techniques.

Diversifying Trends

A new method is proposed for disentangling the systematic components from the idiosyncratic components of risk associated with trend-following strategies. A simple statistical approach combined with standard dimension reduction techniques enables to identify the common trending component of futures market prices. This methodology is applied to a large set of futures, covering all asset classes, to extract a common risk factor, called CoTrend. It is shown that common trends are higher for some cross-asset class pairs than for intra-asset class pairs, such as JPY/USD and Gold. This result is used to create sectors in a portfolio diversification context, especially for trend-following strategies. Additionally, the CoTrend factor helps understand arbitrage-based Hedge Fund strategies, which by essence are decorrelated from standard risk factors.

Index-Aware Model-Order Reduction for a Special Class of Nonlinear Differential-Algebraic Equations

We extend the index-aware model-order reduction method to systems of nonlinear differential-algebraic equations with a special nonlinear term mathbf{f}(mathbf{E}mathbf{x}), where mathbf{E} is a singular matrix. Such nonlinear differential-algebraic equations arise, for example, in the spatial discretization of the gas flow in pipeline networks. In practice, mathematical models of real-life processes pose challenges when used in numerical simulations, due to complexity and system size. Model-order reduction aims to eliminate this problem by generating reduced-order models that have lower computational cost to simulate, yet accurately represent the original large-scale system behavior. However, direct reduction and simulation of nonlinear differential-algebraic equations is difficult due to hidden constraints which affect the choice of numerical integration methods and model-order reduction techniques. We propose an extension of index-aware model-order reduction methods to a special class of nonlinear differential-algebraic equations without any kind of linearization. The proposed model-order reduction approach involves automatic decoupling of nonlinear differential-algebraic equations into nonlinear ordinary differential equations and algebraic equations, based on the decoupling of the linear differential equations obtained by ignoring the nonlinear term, thanks to an additional structural condition. This allows applying standard model-order reduction techniques to both parts without worrying about the index. The same procedure can also be used to simulate nonlinear differential-algebraic equations by standard integration schemes.

New Minimally Invasive Intraoral Procedure for Condylar Fractures: Clinical Presentation and Considerations on Current Techniques.

Mandibular fractures are the third most prevalent maxillofacial traumatic events. Surgical approaches to the condyle are a debated topic. This study describes a mini-invasive technique for condylar fracture reduction. The patient of this study suffered multiple traumatic injuries including a carotid artery dissecting aneurysm, which contraindicated the standard open reduction and internal fixation technique. The novel minimally invasive technique involves intraoral access and fracture fragment realignment using a periosteal elevator, a molar occlusal splint, and intermaxillary fixation after intraoperative radiologic imaging confirmation of condyle reposition.The approach avoids skin incisions and tissue dissection, with good aesthetic outcomes and facial nerve preservation. This technique proved to be safe and simple to be less demanding for the patient, with a shorter recovery time than experienced with other techniques.The results suggest this technique is a good option for the surgical treatment of condylar neck fractures showing favorable rim morphology with primary stability after reduction.

Data-driven phase-isostable reduction for optimal nonfeedback stabilization of cardiac alternans.

Phase-isostable reduction is an emerging model reduction strategy that can be used to accurately replicate nonlinear behaviors in systems for which standard phase reduction techniques fail. In this work, we derive relationships between the cycle-to-cycle variance of the reduced isostable coordinates for systems subject to both additive white noise and periodic stimulation. Using this information, we propose a data-driven technique for inferring nonlinear terms of the phase-isostable coordinate reduction framework. We apply the proposed model inference strategy to the biologically motivated problem of eliminating cardiac alternans, an arrhythmia that is widely considered to be a precursor to more deadly cardiac arrhythmias. Using this strategy, by simply measuring a series of action potential durations in response to periodic stimulation, we are able to identify energy-optimal, nonfeedback control inputs to stabilize a period-1, alternans-free solution.

Clinical Faceoff: The Complex Tibial Plafond Fracture: ORIF or Circular External Fixation?

Clinical Faceoff: The Complex Tibial Plafond Fracture: ORIF or Circular External Fixation?

Efficient Variance Reduction with Least-Squares Monte Carlo Pricing

This paper examines the efficiency of standard variance reduction techniques across option characteristics when pricing American-style call and put options with the Least-Squares Monte Carlo algorithm of Longstaff & Schwartz (2001). Our numerical experiments evaluate the efficiency of antithetic sampling, control variates, importance sampling, and combinations thereof. Whereas most of the American option pricing literature has focused on either put or call options individually, we employ the symmetry relation of McDonald & Schroder (1998) to compare performance for pairs of call and put options whose solution coincide. Our results first show that variance reduction is generally more efficient for put than call options and that control variates is the most efficient stand-alone method. We also find that marginal gains in efficiency are typically achieved by combining variance reduction techniques, though some techniques may interact conflictingly. Finally, since valuation of American-style call options can be improved by pricing symmetric put options instead (Stentoft 2019), we demonstrate that drastic reductions in the standard deviation of the call is obtained by combining all three variance reduction techniques in a symmetric pricing approach, which reduces the standard deviation by a factor of over 20 for long maturity call options on highly volatile assets.

Reduction of Neglected Displaced Fractures of the Distal Femoral Physis.

We performed open osteoclasis, soft-tissue release, and fracture fragment reduction and fixation to treat 10 cases of neglected physeal fractures of the distal aspect of the femur with severe deformity. To our knowledge, no specific surgical procedure for this problem has been reported in the literature. The procedure is typically performed through an extensile anterolateral approach. With use of an osteotome, the typically abundant fracture callus is disrupted and partially removed to recreate the original fracture line. Through periosteal dissection, an extensive musculoperiosteal detachment and release is achieved to facilitate fracture reduction while protecting the physis from further injury. Knee rehabilitation in closed, nondisplaced or minimally displaced fractures1.Open callus osteoclasis in combination with a Z-shaped quadriceps tenoplasty, reduction, and plaster cast immobilization2.Open subperiosteal osteoclasis, reduction, and tibial traction3.Open callus osteoclasis, reduction, and condylar plating4.Sequestrectomy with preservation of a periosteal sleeve to treat osteomyelitis complicating an open fracture1.Transfemoral amputation to treat gas gangrene or vascular injury following severe open injury1,5-7. This procedure was developed in remote medical facilities where patients are often first seen >21 days after the original injury. By that time, closed reduction or standard open reduction and internal fixation techniques are no longer possible. After 6 months of fracture age, the procedure is inefficient. This procedure allows correction of limb malalignment and shortening while preserving the growth plate1. In some cases, hypertrophic fracture callus might be mistaken for the femoral diaphysis.An extensive musculoperiosteal release will facilitate reduction of the fracture fragments.The adequacy of reduction must be assessed in all 3 planes intraoperatively.The adequacy of reduction must be assessed in all 3 planes intraoperatively.The adequacy of reduction must be assessed in all 3 planes intraoperatively.

Radio telescope total power mode: improving observation efficiency

Aims. Radio observing efficiency can be improved by calibrating and reducing the observations in total power mode rather than in frequency, beam, or position-switching modes. Methods. We selected a sample of spectra obtained from the Institut de Radio-Astronomie Millimétrique (IRAM) 30-m telescope and the Green Bank Telescope (GBT) to test the feasibility of the method. Given that modern front-end amplifiers for the GBT and direct Local Oscillator injection for the 30 m telescope provide smooth pass bands that are a few tens of megahertz in width, the spectra from standard observations can be cleaned (baseline removal) separately and then co-added directly when the lines are narrow enough (a few km s−1), instead of performing the traditional ON minus OFF data reduction. This technique works for frequency-switched observations as well as for position- and beam-switched observations when the ON and OFF data are saved separately. Results. The method works best when the lines are narrow enough and not too numerous so that a secure baseline removal can be achieved. A signal-to-noise ratio improvement of a factor of √2 is found in most cases, consistent with theoretical expectations. Conclusions. By keeping the traditional observing mode, the fallback solution of the standard reduction technique is still available in cases of suboptimal baseline behavior, sky instability, or wide lines, and to confirm the line intensities. These techniques of total-power-mode reduction can be applied to any radio telescope with stable baselines as long as they record and deliver the ONs and OFFs separately, as is the case for the GBT.

Quasi phase reduction of all-to-all strongly coupled λ-ω oscillators near incoherent states.

The dynamics of an ensemble of N weakly coupled limit-cycle oscillators can be captured by their N phases using standard phase reduction techniques. However, it is a phenomenological fact that all-to-all strongly coupled limit-cycle oscillators may behave as "quasiphase oscillators," evidencing the need of novel reduction strategies. We introduce, here, quasi phase reduction (QPR), a scheme suited for identical oscillators with polar symmetry (λ-ω systems). By applying QPR, we achieve a reduction to N+2 degrees of freedom: N phase oscillators interacting through one independent complex variable. This "quasi phase model" is asymptotically valid in the neighborhood of incoherent states, irrespective of the coupling strength. The effectiveness of QPR is illustrated in a particular case, an ensemble of Stuart-Landau oscillators, obtaining exact stability boundaries of uniform and nonuniform incoherent states for a variety of couplings. An extension of QPR beyond the neighborhood of incoherence is also explored. Finally, a general QPR model with N+2M degrees of freedom is obtained for coupling through the first M harmonics.

Clinical Outcome of Bimalleolar Ankle Fracture in Patients with Diabetes Mellitus

Category:Trauma; AnkleIntroduction/Purpose:Diabetes is a risk factor of postoperative complication for fracture surgery. The purpose of this study was to evaluate the clinical outcome of bimalleolar ankle fracture in patients with diabetes mellitus.Methods:Twenty two patients (an average age; 69.3 years, an average HbA1C; 7.6%) with bi-malleolar ankle Fracture received open reduction and internal fixation between March 2013 and January 2019. Complications related to surgery, progression to Charcot arthropathy, presence of nonunion were used for outcome analysis. The patients were followed for an average of 12.1 months.Results:The nonunion rate was 4.5% (1 case over 22 cases). The incidence rate of Charcot arthropathy was 4.5% (1 case over 22 cases). The patient with Charcot arthropathy was conversed to the tibiotalarcalcaneal fusion with retrograde intramedullary nail. No wound infection or soft tissue complications related to surgery was reported.Conclusion:Standard open reduction and internal fixation technique showed high union rate of bimalleolar ankle fracture in patients with diabetes mellitus. The surgeon should be cautious to the Charcot arthropathy when treating ankle fracture with diabetes mellitus.

Multiparameter Model Order Reduction for Thermal Modeling of Power Electronics

In this article, a multiparameter model order reduction (MOR) is applied to the thermal modeling and simulation of power electronics modules and air cooling systems. Although widely employed, simulation tools based on finite elements (FE) or finite difference methods result in computationally expensive models that hamper the analysis in studies where one or more parameters are changed. MOR techniques can be applied to reduce the computational complexity. However, standard reduction techniques cannot easily consider parameters variability and need to be reapplied for each parameter value. This article proposes a multiparameter order reduction technique that can significantly improve the thermal simulation efficiency without having a significant impact on the prediction accuracy. The method is applied to multichip SiC power module mounted on a forced air-cooled finned heatsink with variable air flow.

Development of the Thalassaemia Adult Life Index (ThALI)

BackgroundBeta Thalassaemia Major (βTM) is a chronic genetic illness whereby the challenges faced by patients exposes them to increased risk of psychosocial issues. Despite this, a disease-specific tool to measure the impact of this illness on adult patients has yet to be developed.MethodsIn collaboration with βTM adult patients, this study aimed to develop a comprehensive, disease-specific, easy to use psychometrically sound tool to measure the impact of chelation and transfusion dependent βTM in a cross-cultural patient group in England.The Thalassaemia Life Index (ThALI) was developed in two stages – item generation and pre-testing and item reduction – in collaboration with service users. Recruited adult patients shaped the design of the instrument including its statements and subscales. Standard item reduction techniques were used to develop the instrument.ResultsThe final version of the ThALI encompasses 35 statements and five sub-scales - general physical health, coping, body image, appearance and confidence, social relationships and autonomy. This endorses the multidimensionality of quality of life (QoL). The factor structure of the ThALI is highly stable and its internal consistency is high (alpha = 0.87 for the overall scale; 0.83–0.94 for its subscales). The ThALI has sound scaling assumptions, acceptability and score variability. Content validity was confirmed by experts and service user interviewees. The loadings for the items retained were adequate and the item discriminant validity sound.ConclusionsThe ThALI covers the impact of βTM in adult patients. Preliminary testing shows its multidimensionality to be reliable and valid. The national authentication of the tool with patients treated in Centres of Excellence will aim to provide further evidence regarding the ThALI’s psychometric properties. Once authenticated, the ThALI may be utilised in research and in clinical settings to assess the effects of new therapies and/or interventions from the patients’ perspective to inform practice and/or to identify areas of concern.

Ensemble based technique for the assessment of fetal health using cardiotocograph – a case study with standard feature reduction techniques

Intrauterine fetal hypoxia is one of the leading cause of perinatal mortality and morbidity. This can eventually lead to severe neurological damage like cerebral palsy and in extreme cases to fetal demise. It is thus necessary to monitor the fetus during intrapartum and antepartum period. Cardiotocograph (CTG) as a method of assessing the status of the fetus had been in use for last six decades. Nowadays it is the most widely used non-invasive technique for the continuous monitoring of the fetal heart rate (FHR) and the uterine contraction pressure (UCP). Though its introduction limited the birth related problems, the accuracy of interpretation was hindered by quite a few factors. Different guidelines that are provided for the interpretation are based on crisp logic which fails to capture the inherent uncertainty present in the medical diagnosis. Misinterpretations had led to inaccurate diagnosis which resulted in many medico-legal litigations. The vagueness present in the physician’s evaluation is best modeled using soft-computing based techniques. In this paper authors used the CTG dataset from UCI Irvine Machine Learning Data Repository which contains 2126 data and each data-point is represented by 37 features. Dimensionality of the feature set was reduced using different automated methods as well as manually by the physicians. The resulting data sets were classified using various machine learning algorithms. Aim of this study is to establish which set of features is best suited to give good insight into the status of the fetus and also determine the most effective machine learning technique for this purpose. The accuracy of the outcomes were measured using statistical methods such as sensitivity, specificity, precision, F-Measure, confusion matrix and kappa value. We obtained an accuracy of 99.91% and kappa measure of 0.997 when the feature set was reduced using MRMR.