Miracle-dz/UniFAR-FTUs huggingface dataset:
Postoperative Blood Glucose Levels Predict Infection After Total Joint Arthroplasty

Background: Perioperative hyperglycemia has many etiologies, including medication, impaired glucose tolerance, uncontrolled diabetes mellitus, or stress, the latter of which is common in patients postoperatively. Our study investigated the influence of postoperative blood glucose levels on periprosthetic joint infection after elective total joint arthroplasty to determine a threshold for glycemic control for which surgeons should strive during a patient’s hospital stay. Methods: A single-institution retrospective review was conducted on 24,857 primary total joint arthroplasties performed from 2001 to 2015. Of these, 13,196 had a minimum follow-up of 1 year (mean, 5.9 years). Postoperative day 1 morning blood glucose levels were utilized and were correlated with periprosthetic joint infection, as defined by the International Consensus Group on Periprosthetic Joint Infection. Multivariable analysis was used to determine the influence of several important covariates on infection. An alpha level of 0.05 was used to determine significance. Results: The rate of periprosthetic joint infection increased linearly from blood glucose levels of ≥115 mg/dL. Multivariable analysis revealed that blood glucose levels were significantly associated with periprosthetic joint infection (p = 0.028). The optimal blood glucose threshold to reduce the likelihood of periprosthetic joint infection was 137 mg/dL. The periprosthetic joint infection rate in the entire cohort was 1.59% (1.46% in patients without diabetes compared with 2.39% in patients with diabetes; p = 0.001). There was no significant association between blood glucose level and periprosthetic joint infection in patients with diabetes (p = 0.276), although there was a linear trend. Conclusions: The relationship between postoperative blood glucose levels and periprosthetic joint infection increased linearly, with an optimal cutoff of 137 mg/dL. Immediate and strict postoperative glycemic control may be critical in reducing postoperative complications, as even mild hyperglycemia was significantly associated with periprosthetic joint infection. Level of Evidence: Prognostic Level III. See Instructions for Authors for a complete description of levels of evidence.
Ranitidine Inhibition of Breast Tumor Growth Is B Cell Dependent and Associated With an Enhanced Antitumor Antibody Response

Background The histamine receptor 2 antagonist ranitidine is a commonly used, non-prescription, medication. It limits the development, growth, and metastasis of breast cancers in mouse models of disease. In this study, we examined the role of B cells in this response, the impact of ranitidine on the development of antitumor antibodies and subpopulations of natural killer cells using murine breast cancer models. Methods Peripheral blood granulocyte populations were assessed in both E0771-GFP and 4T1 orthotopic tumor-bearing mice by evaluation of stained blood smears. Antibody responses were assessed both in terms of the levels of anti-GFP antibodies detected by enzyme-linked immunosorbent assay and also by antibody binding to the surface of tumor cells evaluated by flow cytometry. B cell and NK cell populations were examined in the draining lymph nodes and spleens of tumor-bearing animals, by flow cytometry with and without ranitidine treatment. Results Oral ranitidine treatment was not associated with changes in peripheral blood granulocyte populations in tumor-bearing mice. However, ranitidine treatment was associated with the development of enhanced antitumor antibody responses. This was not limited to the tumor setting since ranitidine-treated mice immunized with ovalbumin also demonstrated increased IgG antibody responses. Analysis of B cell populations indicated that while B1 cell populations remained unchanged there was a significant decrease in B2 cells in the tumor-draining inguinal lymph nodes. Notably, ranitidine did not significantly inhibit primary tumor growth in B cell-deficient animals. Examination of NK cell populations revealed a significant decrease in the proportion of intermediately functionally mature NK cells populations (CD27+CD11b−) in ranitidine-treated tumor-bearing mice compared with untreated tumor-bearing controls. Conclusion These data demonstrate an important role for B cells in the enhanced antitumor immune response that occurs in response to ranitidine treatment. Our findings are consistent with a model, whereby ranitidine reduces tumor-associated immune suppression allowing for the development of more effective antitumor responses mediated by B cells which may include the participation of NK cells. These data underline the importance of considering widely used histamine receptor antagonists as modulators of antitumor immunity to breast cancer.
An Inverse-Sinusoidal PWM Technique to Improve Thermal Performance of IGBT Module

In this paper, the technique called harmonic-injected, variable-frequency, and inverse-sinusoidal-carrier-based pulse width modulation (HI-VF-ISPWM) has been proposed and implemented on a two-level IGBT voltage source inverter (VSI). The proposed PWM method has been derived using mathematical expressions. The main advantage concerning thermal performance has been experimentally demonstrated and compared with other well-documented PWM methods on the VSI under comparable fundamental load currents with the same number of pulses per cycle. The results show that over 10.6% case temperature improvement of the IGBT power module can be obtained with the HI-VF-ISPWM technique. Moreover, with further optimization of carrier frequency, the harmonic contents are expected to be improved.
HIF-1, Metabolism, and Diabetes in the Embryonic and Adult Heart

The heart is able to metabolize any substrate, depending on its availability, to satisfy its energy requirements. Under normal physiological conditions, about 95% of ATP is produced by oxidative phosphorylation and the rest by glycolysis. Cardiac metabolism undergoes reprograming in response to a variety of physiological and pathophysiological conditions. Hypoxia-inducible factor 1 (HIF-1) mediates the metabolic adaptation to hypoxia and ischemia, including the transition from oxidative to glycolytic metabolism. During embryonic development, HIF-1 protects the embryo from intrauterine hypoxia, its deletion as well as its forced expression are embryonically lethal. A decrease in HIF-1 activity is crucial during perinatal remodeling when the heart switches from anaerobic to aerobic metabolism. In the adult heart, HIF-1 protects against hypoxia, although its deletion in cardiomyocytes affects heart function even under normoxic conditions. Diabetes impairs HIF-1 activation and thus, compromises HIF-1 mediated responses under oxygen-limited conditions. Compromised HIF-1 signaling may contribute to the teratogenicity of maternal diabetes and diabetic cardiomyopathy in adults. In this review, we discuss the function of HIF-1 in the heart throughout development into adulthood, as well as the deregulation of HIF-1 signaling in diabetes and its effects on the embryonic and adult heart.
Layer-Adaptive Communication and Collaborative Transformed-Domain Representations to Optimize Performance in Next-Generation WSNs

In this paper, we combat the problem of performance optimization in wireless sensor networks of next-generation and beyond. Specifically, a novel framework is proposed to handle two major research issues. Firstly, we optimize the utilization of resources available to various sensing nodes. This is achieved via proposed optimal network clustering enriched with layer-adaptive 3-tier communication mechanism to diminish energy holes. We also introduce a mathematical coverage model that helps us minimize the number of coverage holes. Secondly, we present a novel approach to recover the corrupted data received over noisy wireless channels. A robust sparse-domain based recovery method equipped with specially developed averaging filter is used to take care of the unwanted noisy components added to the data samples. Our proposed framework provides a handy routing protocol that enjoys remarkable computation complexity and elongated network lifetime as demonstrated with the help of extensive simulation results.
Comparison of unpleasant and pain thresholds of thermal stimuli in the orofacial regions: a psychophysical study using quantitative sensory testing in healthy young men

Abstract Purpose/Aim: To gain a better understanding of the psychophysics of thermal pain perception in a clinical setting, this study investigated whether thermal thresholds of unpleasantness are different from pain thresholds of cold and heat stimuli. Of particular interest was the relationship between unpleasantness and pain thresholds for cold vs heat stimuli. Material and methods: Thirty healthy male volunteers (mean age 26.1 years, range 23 to 32 years) participated. Thermal detection, cold pain (CPT) and heat pain (HPT) thresholds were measured at 5 trigeminal sites by the method of limits using quantitative sensory testing (QST), followed by cold unpleasant (CUT) and heat unpleasant (HUT) thresholds. Results: The temperatures at which individuals first reported thermal sensations as unpleasant or painful substantially differed among subjects. CUT exhibited a higher mean value with less variability than CPT, and HUT presented a lower mean than HPT (p < .001). As with CPT, CUT did not show any significant difference between the test sites. On the other hand, HUT, like HPT, exhibited site differences (p < .001). There was moderate correlation between CUT and CPT, whereas HUT and HPT were strongly correlated. The relationship between unpleasant and pain thresholds of cold vs heat stimuli was significantly different even when controlling for test site variability (p < .001). Conclusion: These findings indicate that unpleasant and pain thresholds to thermal stimuli differ in healthy young men. Of particular note is the distinct relationship of unpleasant and pain thresholds of cold vs heat stimuli, revealing the thermal difference in temperature transition from unpleasantness to pain.
Tissue-Specific Roles of NKT Cells in Tumor Immunity

NKT cells are an unusual population of T cells recognizing lipids presented by CD1d, a non-classical class-I-like molecule, rather than peptides presented by conventional MHC molecules. Type I NKT cells use a semi-invariant T cell receptor and almost all recognize a common prototype lipid, α-galactosylceramide (α-GalCer). Type II NKT cells are any lipid-specific CD1d-restricted T cells that use other receptors and generally don’t recognize α-GalCer. They play important regulatory roles in immunity, including tumor immunity. In contrast to type I NKT cells that most have found to promote antitumor immunity, type II NKT cells suppress tumor immunity and the two subsets cross-regulate each other, forming an immunoregulatory axis. They also can promote other regulatory cells including regulatory T cells (Tregs) and myeloid-derived suppressor cells (MDSCs), and can induce MDSCs to secrete TGF-β, one of the most immunosuppressive cytokines known. In some tumors, both Tregs and type II NKT cells can suppress immunosurveillance, and the balance between these is determined by a type I NKT cell. We have also seen that regulation of tumor immunity can depend on the tissue microenvironment, so the same tumor in the same animal in different tissues may be regulated by different cells, such as type II NKT cells in the lung vs Tregs in the skin. Also, the effector T cells that protect those sites when Tregs are removed do not always act between tissues even in the same animal. Thus, metastases may require different immunotherapy from primary tumors. Newly improved sulfatide-CD1d tetramers are starting to allow better characterization of the elusive type II NKT cells to better understand their function and control it to overcome immunosuppression.
A nk pm m-Order Harmonic Repetitive Control Scheme with Improved Stability Characteristics

In many applications, the ability to impose periodic reference signals is required for the good operation of the system, making repetitive controllers viable candidates for performing this task. If the reference signal contains only a periodic set of the harmonic components, conventional repetitive controllers can be substituted by nk pm m RC, which are advantageous in terms of response time and memory storage. In this sense, this article proposes a nk pm m RC with better stability characteristics when compared with the previously presented solutions in the literature. The proposed controller was validated through experimental results using a three-phase active power filter.
Risk-Sensitive Generative Adversarial Imitation Learning

We study risk-sensitive imitation learning where the agent’s goal is to perform at least as well as the expert in terms of a risk profile. We first formulate our risk-sensitive imitation learning setting. We consider the generative adversarial approach to imitation learn- ing (GAIL) and derive an optimization problem for our formulation, which we call it risk- sensitive GAIL (RS-GAIL). We then derive two different versions of our RS-GAIL optimization problem that aim at matching the risk profiles of the agent and the expert w.r. t. Jensen-Shannon (JS) divergence and Wasserstein distance, and develop risk-sensitive generative adversarial imitation learning algorithms based on these optimization problems. We evaluate the performance of our algorithms and compare them with GAIL and the risk-averse imitation learning (RAIL) algorithms in two MuJoCo and two OpenAI classical control tasks.
Origin of Nb2O5 Lewis Acid Catalysis for Activation of Carboxylic Acids in the Presence of a Hard Base

Abstract The Nb2O5 surface catalyzes the amidation of carboxylic acids with amines through Nb5+ Lewis acid activation of the C=O group. In this work, DFT calculations were applied to theoretically investigate the C=O bond activation of a model carboxylic acid (acetic acid) on θ‐Al2O3(110), anatase TiO2(101), and T‐Nb2O5(100) surfaces. The adsorption sites, adsorption energies, reaction energy barriers, electronic properties, and vibrational frequency of acetic acid were examined in detail. It was found that the bond activation of the carbonyl group is most efficient on Nb2O5, although the adsorption energy is larger on Al2O3 and TiO2. The most efficient C=O bond activation on Nb2O5 results in the lowest energy barrier of C−N bond formation during amidation. The Nb2O5 surface also shows larger tolerance to methylamine and water molecules than Al2O3 and TiO2 surfaces. These crucial factors contribute to the highest amidation catalytic reactivity on Nb2O5. Furthermore, the position of the mean density of states of the d‐conduction band of the active metal site relative to the Fermi energy level correlates well with the efficiency in the C=O bond activation and, consequently, the catalytic activity for amidation. These results suggest that, unlike a classical understanding of strong acid sites of metal oxide surfaces, interaction of a carbonyl HOMO with an unoccupied metal d‐orbital, or, in other words, covalent‐like interaction between a carbonyl group and metal adsorption site, is relevant to the present system.
Multimodal Deep Neural Networks using Both Engineered and Learned Representations for Biodegradability Prediction

Deep learning algorithms excel at extracting patterns from raw data, and with large datasets, they have been very successful in computer vision and natural language applications. However, in other domains, large datasets on which to learn representations from may not exist. In this work, we develop a novel multimodal CNN-MLP neural network architecture that utilizes both domain-specific feature engineering as well as learned representations from raw data. We illustrate the effectiveness of such network designs in the chemical sciences, for predicting biodegradability. DeepBioD, a multimodal CNN-MLP network is more accurate than either standalone network designs, and achieves an error classification rate of 0.125 that is 27% lower than the current state-of-the-art. Thus, our work indicates that combining traditional feature engineering with representation learning can be effective, particularly in situations where labeled data is limited.
Malware Coordination using the Blockchain: An Analysis of the Cerber Ransomware

In order for malicious software to receive configuration information or commands, malware needs to be able to locate and connect to its owner. As hard-coded addresses are easy to block and thus render the malware installation inoperable, malware writers have turned to dynamically generated addresses. Domain generation algorithms (DGA) generate a list of candidate domain names, each valid for only a short time, at which the malware installation searches for its command & control (C&C) server. As DGAs generate a large list of potential domains - out of which one or a few is actually in use –, they leave a characteristic trace of many failed DNS lookups (NXDomain) in the network, and in result most DGAs can be efficiently detected. In this paper we describe an entirely new principle of domain generation, actively deployed in the Cerber ransomware, which finds and coordinates with its owner based on transaction information in the bitcoin blockchain. This allows the malware author to dynamically update the location of the server in realtime, and as the malware directly goes to the right location no longer generates a sequence of NXDomain responses. We describe the concept of coordination via the blockchain, and report results on a year-long observation of the assets used in the Cerber campaign.
Outcomes Following Modified Tympanomastoidectomy With Soft-wall Reconstruction.

OBJECTIVE To report outcomes following modified tympanomastoidectomy with soft-wall reconstruction (MTMSWR). STUDY DESIGN Retrospective cohort. SETTING Tertiary referral center. PATIENTS Forty-seven patients (48 ears) with aggressive cholesteatoma undergoing MTMSWR. INTERVENTIONS Canal wall down (CWD) tympanomastoidectomy with temporalis fascia reconstruction of the posterior external auditory canal (EAC). MAIN OUTCOME MEASURES Cholesteatoma recidivism; hearing outcomes; degree of soft-wall retraction; time to epithelialization; otorrhea. RESULTS All ears had some form of ossicular compromise. There were 41 ears with completed surveillance of which 39% demonstrated recidivism for cholesteatoma. Of these, 68.8% had a small cholesteatoma foci averaging 3.7 mm. Air pure-tone average remained stable or improved for 60.0% and declined ≤ 20 dB for 85.7%. Excluding ears unable to undergo ossicular chain reconstruction, final air-bone gap was ≤ 30 dB for 66.7%. Retraction of the reconstructed wall was absent-to-mild in 34.7% and moderate-to-full in 52.1%. Thirteen percent had soft-wall breakdown. Average time to full epithelialization of the wall was 58.5 days. CONCLUSIONS MTMSWR is an option for restoring the posterior EAC wall following CWD surgery. Recidivism is comparable to canal wall up surgery, and hearing outcomes are generally better than CWD. Other advantages include rapid epithelialization, low rates of otorrhea, and restoration of a self-cleaning EAC regardless of retraction into the mastoid cavity.
Cutaneous Tuberculosis: Clinicopathologic Arrays and Diagnostic Challenges

The clinicopathological manifestations of cutaneous tuberculosis are diverse. The precise diagnosis is often overlooked, due to clinical presentations as those of cutaneous diseases with different etiology and the relative paucity of the pathogens in the lesions. Meanwhile, almost all of the diagnostic methods confer lower sensitivity and specificities which augments further diagnostic challenges. This article revises the current scenario of the disease's physiopathology and underscores clinicopathological challenges, due to multifaceted presentations of cutaneous tuberculosis, in the diagnosis.
A Modular Medium Voltage IGCT Gate Driver Supply

This paper introduces a novel concept for use as a medium voltage IGCT gate driver supply. The concept makes use of an integrated magnetic structure to transmit orthogonal signals for power and control, and a multiple output LCC converter built around it. The concept is modular and fault tolerant. It can convert the dc bus voltage in an IGCT-based system into multiple independently isolated outputs, where normally two converter systems are used. This contributes to efficiency and cost effectiveness. In addition to introducing the concept, a number of design parameters are optimized for a number of cases and simulations are performed, demonstrating its potential. Targeted applications are IGCT-based modular multilevel converters.
Robust ghost-free multiexposure fusion for dynamic scenes

Abstract. Ghosts always appear in the multiexposure fusion for dynamic scenes. Most of the existing deghosting methods require complicated and subjective parameter settings, easily resulting in many artifacts. A robust exposure fusion method that removes ghosts while preserving the details of the image is presented. The proposed method first detects the motion area by bidirectional intensity mapping and calculates the motion weight. Then, the latent images are generated by weighted optimization in gradient domain, and ghosts are removed automatically. After removing the ghosts, fusion weights are calculated using a patch-based fusion method, and exposure fusion is performed with details retained and outlier values suppressed. Experiments show that the proposed method can remove ghosts effectively, which demonstrates strong robustness to ghosts in a variety of circumstances. It also avoids influence from complicated and subjective parameter settings.
Interplay of multiple pathways and activity-dependent rules in STDP

Hebbian plasticity describes a basic mechanism for synaptic plasticity whereby synaptic weights evolve depending on the relative timing of paired activity of the pre- and postsynaptic neurons. Spike-timing-dependent plasticity (STDP) constitutes a central experimental and theoretical synaptic Hebbian learning rule. Various mechanisms, mostly calcium-based, account for the induction and maintenance of STDP. Classically STDP is assumed to gradually emerge in a monotonic way as the number of pairings increases. However, non-monotonic STDP accounting for fast associative learning led us to challenge this monotonicity hypothesis and explore how the existence of multiple plasticity pathways affects the dynamical establishment of plasticity. To account for distinct forms of STDP emerging from increasing numbers of pairings and the variety of signaling pathways involved, we developed a general class of simple mathematical models of plasticity based on calcium transients and accommodating various calcium-based plasticity mechanisms. These mechanisms can either compete or cooperate for the establishment of long-term potentiation (LTP) and depression (LTD), that emerge depending on past calcium activity. Our model reproduces accurately the striatal STDP that involves endocannabinoid and NMDAR signaling pathways. Moreover, we predict how stimulus frequency alters plasticity, and how triplet rules are affected by the number of pairings. We further investigate the general model with an arbitrary number of pathways and show that depending on those pathways and their properties, a variety of plasticities may emerge upon variation of the number and/or the frequency of pairings, even when the outcome after large numbers of pairings is identical. These findings, built upon a biologically realistic example and generalized to other applications, argue that in order to fully describe synaptic plasticity it is not sufficient to record STDP curves at fixed pairing numbers and frequencies. In fact, considering the whole spectrum of activity-dependent parameters could have a great impact on the description of plasticity, and a better understanding of the engram.