Miracle-dz/UniFAR-FTUs huggingface dataset:
Classification and interaction in random forests

Suppose you are a physician with a patient whose complaint could arise from multiple diseases. To attain a specific diagnosis, you might ask yourself a series of yes/no questions depending on observed features describing the patient, such as clinical test results and reported symptoms. As some questions rule out certain diagnoses early on, each answer determines which question you ask next. With about a dozen features and extensive medical knowledge, you could create a simple flow chart to connect and order these questions. If you had observations of thousands of features instead, you would probably want to automate. Machine learning methods can learn which questions to ask about these features to classify the entity they describe. Even when we lack prior knowledge, a classifier can tell us which features are most important and how they relate to, or interact with, each other. Identifying interactions with large numbers of features poses a special challenge. In PNAS, Basu et al. (1) address this problem with a new classifier based on the widely used random forest technique. The new method, an iterative random forest algorithm (iRF), increases the robustness of random forest classifiers and provides a valuable new way to identify important feature interactions. Random forests came into the spotlight in 2001 after their description by Breiman (2). He was largely influenced by previous work, especially the similar “randomized trees” method of Amit and Geman (3), as well as Ho’s “random decision forests” (4). Random forests have since proven useful in many fields due to their high predictive accuracy (5, 6). In biology and medicine, random forests have successfully tackled a range of problems, including predicting drug response in cancer cell lines (7), identifying DNA-binding proteins (8), and localizing cancer to particular tissues from a liquid biopsy (9). Random forests have also … [↵][1]1To whom correspondence should be addressed. Email: michael.hoffman{at}utoronto.ca. [1]: #xref-corresp-1-1
Evidence of Inbreeding Depression on Human Height

Stature is a classical and highly heritable complex trait, with 80%–90% of variation explained by genetic factors. In recent years, genome-wide association studies (GWAS) have successfully identified many common additive variants influencing human height; however, little attention has been given to the potential role of recessive genetic effects. Here, we investigated genome-wide recessive effects by an analysis of inbreeding depression on adult height in over 35,000 people from 21 different population samples. We found a highly significant inverse association between height and genome-wide homozygosity, equivalent to a height reduction of up to 3 cm in the offspring of first cousins compared with the offspring of unrelated individuals, an effect which remained after controlling for the effects of socio-economic status, an important confounder (χ2 = 83.89, df = 1; p = 5.2×10−20). There was, however, a high degree of heterogeneity among populations: whereas the direction of the effect was consistent across most population samples, the effect size differed significantly among populations. It is likely that this reflects true biological heterogeneity: whether or not an effect can be observed will depend on both the variance in homozygosity in the population and the chance inheritance of individual recessive genotypes. These results predict that multiple, rare, recessive variants influence human height. Although this exploratory work focuses on height alone, the methodology developed is generally applicable to heritable quantitative traits (QT), paving the way for an investigation into inbreeding effects, and therefore genetic architecture, on a range of QT of biomedical importance.
IBOM: An Integrated and Balanced On-Chip Memory for High Performance GPGPUs

GPGPU accelerated computing has revolutionized a broad range of applications. To serve between the ever-growing computing capability and external memory, the on-chip memory is becoming increasingly important to GPGPU performance for general-purpose computing. Inherited from the traditional CPUs, however, the contemporary GPGPU on-chip memory design is suboptimal to the SIMT (single instruction, multiple threads) execution. In particular, the on-chip first-level data (L1D) cache thrashing, resulting from insufficient capacity and imbalanced usage, leads to a low hit rate and limits the overall performance. In this study, we reform the contemporary on-chip memory design and propose an integrated and balanced on-chip memory (IBOM) architecture for high-performance GPGPUs. It first virtually enlarges the L1D cache size by an integrated architecture that exploits the under-utilized register file (RF) with lightweight ISA, compiler and microarchitecture supports. Then with sufficient capacity, it is able to improve the cache usage by a set balancing technique that exploits the under-utilized set resources. In our proposed IBOM design, the register and cache accesses are amenable to normal pipeline operations with simple changes. It adequately exploits the size inversion in GPGPU on-chip memory, and enables optimized utilization of the precious resources for higher performance and energy efficiency with even smaller on-chip memory size. The experiment results demonstrate that the proposed IBOM design can offer an average of 29.6 percent increase in L1D hit rate and in turn 3X performance improvement for the cache-sensitive applications.
Sustained exercise-trained juvenile black carp (Mylopharyngodon piceus) at a moderate water velocity exhibit improved aerobic swimming performance and increased postprandial metabolic responses

ABSTRACT The objectives of this study were to examine whether sustained exercise training at four water velocities, i.e. nearly still water (control), 1 body length (BL) s−1, 2 BL s−1 and 4 BL s−1, has effects on swimming performance and digestive metabolism in juvenile black carp (Mylopharyngodon piceus). The results demonstrated that fish subjected to sustained training at 2 and 4 BL s−1 showed significantly higher critical swimming speed (Ucrit) and maximum metabolic rate (MMR) over the control group. Fish subjected to sustained training at 1 and 2 BL s−1 showed a significantly (30 and 54%) prolonged duration, 14 and 17% higher postprandial ṀO2 increment (i.e. ṀO2peak), and 62 and 92% more energy expended on specific dynamic action (SDA), respectively, after consuming a similar meal over fish kept in nearly still water. These results suggest that (1) sustained exercise training at a higher speed (2 or 4 BL s−1) had a positive influence on the aerobic swimming performance of juvenile M. piceus, which may be associated with improved aerobic metabolism; and (2) sustained exercise training at a lower speed (1 or 2 BL s−1) resulted in elevated postprandial metabolic responses in juvenile M. piceus. Summary: Sustained exercise training at a moderate water velocity had positive effects on aerobic swimming performance and postprandial metabolic responses in juvenile black carp (Mylopharyngodon piceus).
Upstream and downstream analysis of an optical fronthaul system based on DSP-assisted channel aggregation

In this paper,we focus on a well-known optical fronthauling architecture based on frequency division multiplexed digital signal processing (DSP)-assisted channel aggregation, and we present new results related to the optimization of the optical setup, proposing an efficient technique for the optimization of the transmission. In particular, we report an original pre-emphasis technique to equalize the performance of the radio channels, especially focusing on the upstream (US) link that has more critical characteristics but has not typically been treated in detail in previous works on this topic. The effects of both radio and optical impairments on the error vector magnitude (EVM) are taken into account. An analytical description of our approach is provided, and then it is applied on an experimental setup (able to aggregate up to 96 20-MHz radio signals), showing the possibility of minimizing the maximum EVM at the output of the fronthauling link, for both downstream and US transmission. Additionally, a low complexity technique to practically estimate the EVM per channel by taking advantage of only the DSPaggregation/ deaggregation functionalities is proposed and, again, experimentally demonstrated.
Stability Analysis and State-Feedback Control of LPV Systems With Piecewise Constant Parameters Subject to Spontaneous Poissonian Jumps

Linear parameter-varying systems with piecewise constant parameters subject to spontaneous Poissonian jumps are a class of systems that does not seem to have been thoroughly considered in the literature. We partially fill this gap here by providing sufficient stability and performance analysis conditions stated in terms of infinite-dimensional LMI problems that can be solved using sum of squares programming. A particularity of the obtained conditions lies in the presence of an integral term leading to some technical difficulties when attempting to obtain convex conditions for the design of a gain-scheduled state-feedback controller. This difficulty is circumvented by relying on a recent result for time-delay systems analysis and an equivalent integral-free LMI condition is obtained. The approach is illustrated through several examples.
Efficacy of Epidural Analgesia after Laparotomy in Children

Abstract Background Epidural analgesia (EDA) is used as postoperative pain treatment in children, but little is known about its efficacy after laparotomy in children. This retrospective study investigated the efficacy of postoperative EDA after laparotomy in children and the frequencies of adverse effects and complications. Materials and Methods Data of all children aged 0 to 18 years undergoing laparotomy and treated with EDA in our hospital from January 2014 to December 2015 were collected. EDA was classified as successful either if the catheter was removed when there was no further need, and the patient was comfortable with oral/rectal analgesics or when EDA was continued after intervention. Results Ninety children with a median age of 3.7 years were included in the study. In 65% (59/90), EDA was classified as successful. In 34% (20/59) of all successful cases, an additional intervention was needed. In 35% (31/90), the catheter was removed earlier than planned, in half of these cases after an intervention. The primary reason for earlier removal was inadequate analgesia and technical failure. Adverse effects occurred in 18% and complications in 1% of cases. The successful group was significantly younger than the unsuccessful (p = 0.003). Conclusion EDA after laparotomy positively contributed to postoperative pain treatment in two-thirds of children. Numbers of adverse effects and complications were low. It is important to optimize pain management after laparotomy in children; thus, further prospective studies should focus on optimizing EDA and comparing EDA with other techniques of analgesia.
Performance Modeling for Optimal Data Placement on GPU with Heterogeneous Memory Systems

A heterogeneous memory system (HMS) consists of multiple memory components with different properties. GPU is a representative architecture with HMS. It is challenging to decide optimal placement of data objects on HMS because of the large exploration space and complicated memory hierarchy on HMS. In this paper, we introduce performance modeling techniques to predict performance of various data placements on GPU. In essence, our models quantify and capture implicit performance correlation between different data placements. Given the memory access information and performance of a sample data placement, our models predict performance for other data placements based on the quantified correlation. We reveal critical performance factors that cause performance variation across data placements. Those factors include instruction replay, addressing mode, hardware queuing delay of memory requests, off-chip memory access latency, and caching effects. Those factors, which are often not sufficiently considered in the existing performance models, can significantly impact modeling accuracy. We introduce a series of techniques to model those factors. We extensively evaluate our models with a variety of benchmarks with various data placements. Our models are able to quantitatively predict the benefit or performance loss of data placements.
eICIC Configuration Algorithm with Service Scalability in Heterogeneous Cellular Networks

Interference management is one of the most important issues in heterogeneous cellular networks with multiple macro and pico cells. The enhanced inter cell interference coordination (eICIC) has been proposed to protect downlink pico cell transmissions by mitigating interference from neighboring macro cells. Therefore, the adaptive eICIC configuration problem is critical, which adjusts the parameters including the ratio of almost blank subframes (ABS) and the bias of cell range expansion (RE). This problem is challenging especially for the scenario with multiple coexisting network services, since different services have different user scheduling strategies and different evaluation metrics. By using a general service model, we formulate the eICIC configuration problem with multiple coexisting services as a general form consensus problem with regularization and solve the problem by proposing an efficient optimization algorithm based on the alternating direction method of multipliers. In particular, we perform local RE bias adaptation at service layer, local ABS ratio adaptation at BS layer, and coordination among local solutions for a global solution at a network layer. To provide the service scalability, we encapsulate the service details into the local RE bias adaptation subproblem, which is isolated from the other parts of the algorithm, and we also introduce some implementation examples of the subproblem for different services. The extensive simulation results demonstrate the efficiency of the proposed algorithm and verify the convergence property.
Impacts of SRT on Particle Size Distribution and Reactor Performance in Activated Sludge Processes

Particle size distribution of the particulates is an essential characteristic of the wastewater quality. Particle size of activated sludge flocs may affect key sludge handling processes including sedimentation, thickening, digestion, and dewatering. This study evaluated the effects of solids retention time (SRT) on particle size distribution, sludge settleability, effluent turbidity, and removals of chemical oxygen demand (COD) and ‐N in a lab‐scale Modified Ludzak–Ettinger (MLE) reactor and an integrated fixed film activated sludge (IFAS) reactor. This study also surveyed particle size distribution profile of five full‐scale water resource recovery facilities (WRRFs), including high purity oxygen (HPO), step‐feed nitrification/denitrification (NDN), and MLE NDN processes. This study provides direct evidence of the effects of SRT on particle size distribution and sludge settleability in lab‐scale reactors and full‐scale WRRFs.
Speaker Recognition Using e–Vectors

Systems based on i–vectors represent the current state–of–the–art in text-independent speaker recognition. Unlike joint factor analysis (JFA), which models both speaker and intersession subspaces separately, in the i–vector approach all the important variability is modeled in a single low-dimensional subspace. This paper is based on the observation that JFA estimates a more informative speaker subspace than the “total variability” i–vector subspace, because the latter is obtained by considering each training segment as belonging to a different speaker. We propose a speaker modeling approach that extracts a compact representation of a speech segment, similar to the speaker factors of JFA and to i–vectors, referred to as “e–vector. ” Estimating the e–vector subspace follows a procedure similar to i–vector training, but produces a more accurate speaker subspace, as confirmed by the results of a set of tests performed on the NIST 2012 and 2010 Speaker Recognition Evaluations. Simply replacing the i–vectors with e–vectors we get approximately 10% average improvement of the C<inline-formula><tex-math notation="LaTeX"> $_{\text{primary}}$</tex-math></inline-formula> cost function, using different systems and classifiers. It is worth noting that these performance gains come without any additional memory or computational costs with respect to the standard i–vector systems.
Effects of erythropoietin on ischemia, follicular survival, and ovarian function in ovarian grafts.

Ovarian tissue transplantation is performed to preserve fertility in patients undergoing chemotherapy and radiotherapy. However, ischemia/reperfusion (IR) injury and free radical production occurring during the revascularization of the transplanted tissue are the major limitations of this procedure. The aim of this study was to investigate the effect of erythropoietin (EPO) as an antioxidant on oxidative stress and ovary survival following transplantation. The Naval Medical Research Institute (NMRI) mice (4-5 weeks old) were divided into three groups (six mice per group): control; autograft+saline, and autograft+EPO (500 IU/kg i.p.). After 28 days, ovary compartments were estimated stereologically. DNA fragmentation and plasma malondialdehyde (MDA), progesterone, and estradiol (E2) concentrations were also evaluated. The results were analyzed using one-way ANOVA and Tukey's test, and the means were significantly different at P<0.05. The mean total volume of ovary, cortex, and medulla and the number of follicles increased significantly in the autograft+EPO group (P<0.01). Apoptosis rate in the autograft+EPO group was lower than that in the autograft+saline group. The concentration of MDA decreased significantly in the autografted EPO-treated group than in the autografted saline-treated group (P<0.01). The concentration of E2 increased significantly in the autograft+EPO group than in the autograft+saline group (P<0.01). EPO reduced IR injury, increasing follicle survival and function in grafted ovaries. Free Persian abstract A Persian (Farsi) translation of the abstract is freely available online at http://www.reproduction-online.org/content/147/5/733/suppl/DC1.
Prevalence and factors associated with mild cognitive impairment among Chinese older adults with depression

Depression and mild cognitive impairment (MCI) are common among older adults. Most of the existing studies were carried out in developed countries, and evidence from developing countries are lacking. In the present study, using a national sample, we aimed to describe the prevalence of MCI and its associated factors among Chinese older adults with depression.
Comment on “PWM-Based Adaptive Sliding-Mode Control for Boost DC–DC Converters”

The purpose of this paper is to comment on the reference voltage tracking ability of a recently proposed state observer based adaptive sliding mode control for boost converters. It is shown that the control in the cited paper cannot track the reference voltage. A modified control law that enables reference voltage tracking while preserving the other advantages of the commented paper is proposed and validated by simulation and experimentation on laboratory hardware.
Age-related impairment of metabovascular coupling during cortical spreading depolarizations.

Cortical spreading depolarizations (SDs) may lead to long-lasting alterations in cerebral blood flow (CBF), which contribute to neuronal dysfunction and hypoxic tissue injury. There is growing evidence to suggest that age-related structural and functional alterations of the neurovascular unit significantly increase both the incidence of SDs and aggravate their functional consequences. Recent studies suggest that metabolic signaling plays a major role in modulating cerebral blood flow responses evoked by SDs and provide critical evidence that aging considerably weakens metabovascular coupling with SD. As a consequence, the aged brain becomes increasingly more vulnerable to the deleterious effects of SDs.
Design Optimization With Multiphysics Analysis on External Rotor Permanent Magnet-Assisted Synchronous Reluctance Motors

Multiphase permanent magnet-assisted synchronous reluctance motor (PMa-SynRM) is proposed as one of the optimal machine designs for vehicular applications such as electric vehicles due to their fault tolerant operation capability. However, optimization of the multiphase PMa-SynRMs for in-wheel applications in EVs and aircrafts require more research efforts to increase their power density with the size constraint. In addition, optimization of the machine design with multiphysics structural and thermal analysis has not been intensively discussed in the literature. In this paper, an optimal design procedure which includes multiphysics analysis to design the multiphase external rotor PMa-SynRMs is presented. In specific, a five-phase external rotor PMa-SynRM with neodymium-based magnets has been proposed as a solution to produce higher power density compared to the conventional internal rotor PMa-SynRMs. Multiphysics analysis is included in the optimization procedure to determine the effects due to rotational forces and heat flow on the proposed optimal five-phase external rotor PMa-SynRM design. Detailed electromagnetic finite element simulations are carried out to depict the performance characteristics. A 3.8-kW prototype is fabricated and the experimental results are compared with same volume 3-kW five-phase internal rotor PMa-SynRM.
Role of rostral ventrolateral medullary ERK/JNK/p38 MAPK signaling in the pressor effects of ethanol and its oxidative product acetaldehyde.

BACKGROUND We tested the hypothesis that alterations of the phosphorylation/dephosphorylation profile of mitogen-activated protein kinases (MAPKs) in the rostral ventrolateral medulla (RVLM) underlie the pressor response elicited by ethanol (EtOH) microinjection into the RVLM of spontaneously hypertensive rats (SHRs). The studies were extended to determine whether acetaldehyde (ACA), the primary oxidative product of EtOH, replicates the molecular effects of EtOH within the RVLM and the consequent pressor response. METHODS Effects of EtOH or ACA on blood pressure (BP) were evaluated in the absence or presence of selective JNK (SP600125), ERK (PD98059), p38 (SB203580), or ser/thr phosphatases (okadaic acid [OKA]) inhibitor. RESULTS Intra-RVLM EtOH (10 μg/rat) or ACA (2 μg/rat) caused a similar ERK2-dependent pressor response because EtOH or ACA-evoked increases in BP and in RVLM p-ERK2 level were abolished after pharmacologic inhibition of ERK phosphorylation. SP600125 abrogated the pressor action of EtOH, but not ACA, thus implicating JNK in EtOH action on BP. Despite EtOH enhancement of p38 phosphorylation, pharmacological studies argued against a causal role for this kinase in EtOH-evoked pressor response. RVLM phosphatase catalytic activity was not influenced by EtOH or ACA. Interestingly, pharmacologic phosphatase inhibition (OKA), which increased RVLM p-ERK2 and BP, abrogated the pressor effect of subsequently administered EtOH or ACA. CONCLUSIONS Enhancement of RVLM ERK2 phosphorylation constitutes a major molecular mechanism for the pressor response elicited by intra-RVLM EtOH or its metabolite, ACA, in conscious SHRs. Further, RVLM kinases dephosphorylation does not contribute to intra-RVLM EtOH- or ACA-evoked pressor response.