Miracle-dz/UniFAR-FTUs huggingface dataset:
Polymer Nanocomposites in High-Voltage Insulation: The Dielectric Characteristics of Doped Polypropylene

Polymers containing inorganic nanoparticles have been found to exhibit improved to excellent performance for electrical engineering applications. It was found that nanoparticles with surface chemical modifications displayed improved compatibility with the polymer matrix. After tailoring the nanometric interface between the nanoparticles and the polymer matrix and employing the appropriate compounding technique, multifunctional nanocomposites could be prepared.
Interaction between ABCG2 421C>A polymorphism and valproate in their effects on steady‐state disposition of lamotrigine in adults with epilepsy

To investigate the impact of glucuronidation enzyme (UGT1A4*3 142T>G, UGT1A4*2 70C>A, UGT2B7 –161C>T) and transporter (MDR1/ABCB1 1236C>T, ABCG2 421C>A) polymorphisms on steady‐state disposition of lamotrigine and on the lamotrigine–valproate interaction.
Dysfunction of Optineurin in Amyotrophic Lateral Sclerosis and Glaucoma

Neurodegenerative disorders, including amyotrophic lateral sclerosis (ALS), frontotemporal dementia, and glaucoma, affect millions of people worldwide. ALS is caused by the loss of motor neurons in the spinal cord, brainstem, and brain, and genetic mutations are responsible for 10% of all ALS cases. Glaucoma is characterized by the loss of retinal ganglion cells and is the most common cause of irreversible blindness. Interestingly, mutations in OPTN, encoding optineurin, are associated with both ALS and glaucoma. Optineurin is a highly abundant protein involved in a wide range of cellular processes, including the inflammatory response, autophagy, Golgi maintenance, and vesicular transport. In this review, we summarize the role of optineurin in cellular mechanisms implicated in neurodegenerative disorders, including neuroinflammation, autophagy, and vesicular trafficking, focusing in particular on the consequences of expression of mutations associated with ALS and glaucoma. This review, therefore showcases the impact of optineurin dysfunction in ALS and glaucoma.
Trifecta Outcomes in Multifocal Tumors: A Comparison Between Robotic and Open Partial Nephrectomy.

OBJECTIVES To report a comparative analysis of outcomes in patients who underwent multiple excisions for unilateral synchronous multifocal renal tumors using both open and robotic approaches. METHODS We retrospectively reviewed 110 patients who underwent robotic and open partial nephrectomy and had multiple tumor excisions in an ipsilateral kidney. "Trifecta" was defined as negative surgical margins, no urologic complications, and a glomerular filtration rate (GFR) preservation of ≥90% at last follow-up. Inverse probability of treatment weighting (IPTW) was applied to equilibrate treatment groups, minimize selection bias, and optimize inference on the basis of each patient's clinicodemographic characteristics. RESULTS Sixty-eight robotic and 42 open patient approaches had sufficient data for IPTW. After weighting, there were no statistical differences in baseline characteristics between the two groups. On adjusted analyses, robotic partial nephrectomy achieved equivalent rates of trifecta to open surgery (16.3% vs 16.5%, p = 0.99), which persisted on subgroup analyses of patients with two (20.1% vs 23.7%, p = 0.82) or more than two tumors (6.8% vs 7.4%, p = 0.95). There were no differences between robotic and open cohorts for negative margin rates, absence of complications, or GFR ≥90%. The robotic cohort had a shorter mean length of stay (3.4 vs 4.9 days, p < 0.001). CONCLUSIONS Surgical resection remains the mainstay for patients with unilateral, synchronous, and multifocal renal tumors. Our analysis found that both open and robotic approaches to partial nephrectomy are equally likely to achieve the "trifecta" outcome in an equilibrated high-risk group of patients. The robotic approach for these complex patients may be safe and feasible for a carefully selected group of patients.
Accurate Fourth-Order Debye Model for the Head Tissues Across the 0.1–1 GHz Band Using Metaheuristic Genetic Algorithm

Over the past couple of years, there has been a growing interest in implantable medical devices (IMDs) for diagnostic, monitoring, and therapeutic applications. Wireless power transfer (WPT) to IMDs enables the removal of batteries for further miniaturization of the overall IMDs footprint. Accurate modeling of the dielectric properties is therefore essential and inevitable for dosimetry studies to investigate the safety considerations of the WPT to IMDs. In this paper, an accurate fourth-order Debye model is derived based on a metaheuristic genetic algorithm to represent the dispersive nature of the head tissues across the $\text{0.1}\text{--}1\,\text{GHz}$, which includes the popular subbands for IMDs. The 46 head tissues are reduced to 20 tissues based on the similar dielectric properties and categorized into four different groups based on the major organs in the head. The developed Debye model shows a better fitting for the measured data compared with the Cole–Cole model for all the tissue groups. Predominantly, the achieved error function between the measured dielectric properties, and the fitted Debye model is less than 0.07% for tissue groups. In general, a total error reduction of more than 60% is obtained for the developed Debye model compared with the Cole–Cole model for all tissue groups. The proposed Debye model can be incorporated into the available computational methods, such as the finite difference time domain (FDTD) method, to calculate the distribution of the electromagnetic fields inside the brain with more accuracy than the Cole–Cole model.
Distributed Matching Algorithms for Spectrum Access: A Comparative Study and Further Enhancements

In this paper, we consider a spectrum access scenario which consists of two groups of users, namely Primary Users (PUs) and Secondary Users (SUs) in Cooperative Cognitive Radio Networks (CCRNs). SUs cooperatively relay PUs messages based on Amplify-and-Forward (AF) and Decode-and-Forward (DF) cooperative techniques, in exchange for accessing some of the spectrum for their secondary communications. From the literatures, we found that the Conventional Distributed Algorithm (CDA) and Pragmatic Distributed Algorithm (PDA) aim to maximize the PU sum-rate resulting in a lower sum-rate for the SU. In this contribution, we have investigated a suit of distributed matching algorithms. More specifically, we investigated SU-based CDA (CDA-SU) and SU-based PDA (PDA-SU) that maximize the SU sum-rate. We have also proposed the All User-based PDA (PDA-ALL), for maximizing the sum-rates of both PU and SU groups. A comparative study of CDA, PDA, CDA-SU, PDA-SU and PDA-ALL is conducted, and the strength of each scheme is highlighted. Different schemes may be suitable for different applications. All schemes are investigated under the idealistic scenario involving perfect coding and perfect modulation, as well as under practical scenario involving actual coding and actual modulation. Explicitly, our practical scenario considers the adaptive coded modulation based DF schemes for transmission flexibility and efficiency. More specifically, we have considered the Self-Concatenated Convolutional Code (SECCC), which exhibits low complexity, since it invokes only a single encoder and a single decoder. Furthermore, puncturing has been employed for enhancing the bandwidth efficiency of SECCC. As another enhancement, physical layer security has been applied to our system by introducing a unique Advanced Encryption Standard (AES) based puncturing to our SECCC scheme.
Understanding delays in acute stroke care: a systematic review of reviews

Background Stroke is the leading cause of adult long-term disability in Western countries. Intravenous thrombolytic therapy with recombinant tissue plasminogen activator is safe and effective within the first 4.5 h after the onset of stroke. Various factors delaying acute stroke care have been identified in the literature. This review aimed to provide an overview of factors delaying acute stroke care and attempted to show how they interact in a synthetic framework. Methods We conducted a systematic review of literature reviews published in Medline and DORIS until 2016 on factors influencing acute stroke pathway timeframe. Results We analyzed 31 reviews that cover all factors of delays from stroke onset to treatment. We identified 27 factors that had a significant impact on acute stroke care and can be categorized into four distinct categories: patient-related factors, training, resources and lack of coordination. We also reported associations between factors observed in both between categories (mainly between patients and organizational/logistical factors) and within categories. Conclusion This review provides a wide overview of factors influencing acute stroke pathway. Since it was observed that the identified factors were interrelated, they needed to be analyzed in a systematic way. We hence created a synthetic framework that combines several categories of factors while assuming that factor weight varies from a study context to another. Better knowledge on underlying mechanisms between factors would provide crucial improvement of the interventions aiming at reducing delays in both pre-hospital and inhospital stages. For future research, we recommend adopting a systemic perspective on factors influencing acute stroke pathway.
An Innovative Perioperative Pain Program for Chronic Opioid Users: An Academic Medical Center’s Response to the Opioid Crisis

Increased utilization of prescription opioids for pain management has led to a nationwide public health crisis with alarming rates of addiction and opioid-related deaths. In the surgical setting, opioid prescriptions have been implicated as a contributing factor to the opioid epidemic. The authors developed an innovative model to address aspects of pain management and opioid utilization during preoperative evaluation, acute surgical hospitalization, and postoperative follow-up for chronic opioid users. This program involves multidisciplinary teams that include acute and chronic pain specialists, psychiatrists, integrative medicine specialists, and physical medicine and rehabilitation services. It also features a novel infrastructure for triage and pain management education and treatment. Individualized patient plans are devised that can include preoperative opioid weaning, regional anesthesia that minimizes opioid use, and multimodal techniques for surgical pain treatment. Multidisciplinary programs such as this have the potential to both improve perioperative pain control and prevent escalation of opioid use among chronic opioid users.
The relationship between climate change and wars waged between nomadic and farming groups from the Western Han Dynasty to the Tang Dynasty period

Abstract. In ancient China, shifts in regional productivity of agriculture and animal husbandry, caused by climate change, either led to wars or peaceful relations between nomadic and farming groups. During the period spanning the Western Han Dynasty to the Tang Dynasty, 367 wars were waged between these groups. While 69 % of the wars were initiated by nomads, 62.4 % were won by the farming groups. On a centennial timescale, the battlegrounds were mostly in northern areas (at an average latitude of 38.92° N) during warm periods, moving southward (at an average latitude of 34.66° N) during cold periods. On a decadal timescale, warm climates corresponded to a high incidence of wars (a correlation coefficient of 0.293). While farming groups were inclined to initiate wars during dry and cold periods, their chances of achieving victory were reduced at such times. The main reasons for this are, first, that a warm climate provided a solid material foundation for nomadic and farming groups, contributing especially to enhanced productivity among the former. However, the overriding desire of nomadic groups to expand essential subsistence means led to wars. Second, during cold periods, farming groups moved to and settled in the south, while nomadic groups occupied the Central Plain. Thus, the locations of the battlefields also changed. While other factors also influenced these wars, climate change served as a backdrop, playing an indirect role in wars between these groups.
A Hybrid Approach for Detecting Automated Spammers in Twitter

Twitter is one of the most popular microblogging services, which is generally used to share news and updates through short messages restricted to 280 characters. However, its open nature and large user base are frequently exploited by automated spammers, content polluters, and other ill-intended users to commit various cybercrimes, such as cyberbullying, trolling, rumor dissemination, and stalking. Accordingly, a number of approaches have been proposed by researchers to address these problems. However, most of these approaches are based on user characterization and completely disregarding mutual interactions. In this paper, we present a hybrid approach for detecting automated spammers by amalgamating community-based features with other feature categories, namely metadata-, content-, and interaction-based features. The novelty of the proposed approach lies in the characterization of users based on their interactions with their followers given that a user can evade features that are related to his/her own activities, but evading those based on the followers is difficult. Nineteen different features, including six newly defined features and two redefined features, are identified for learning three classifiers, namely, random forest, decision tree, and Bayesian network, on a real dataset that comprises benign users and spammers. The discrimination power of different feature categories is also analyzed, and interaction- and community-based features are determined to be the most effective for spam detection, whereas metadata-based features are proven to be the least effective.
Tättar Unsupervised Machine Translation using Cross-Lingual N-gram Embeddings

The current best machine translation systems have achieved excellent results, but rely heavily on large parallel corpora. There have been many attempts on getting the same good results on low-resource languages, but these tries have been somewhat unsuccessful. In this work, I propose a novel unsupervised machine translation system that uses n-gram embeddings for getting the translations by learning cross-lingual embeddings. This solution requires only monolingual corpora, not a single parallel sentence is needed, which is achieved by using unsupervised word translation. I report my findings for Estonian English Estonian language pair. The solution does not work as well as expected, but tests suggest that it works better than simple word-by-word translation.
Integration of Metabonomics and Transcriptomics Reveals the Therapeutic Effects and Mechanisms of Baoyuan Decoction for Myocardial Ischemia

Myocardial ischemia (MI) is an escalating public health care burden worldwide. Baoyuan decoction (BYD) is a traditional Chinese medicine formula with cardioprotective activity; however, its pharmacological characteristics and mechanisms are obscured. Herein, a multi-omics strategy via incorporating the metabonomics, transcriptomics, and pharmacodynamics was adopted to investigate the effects and molecular mechanisms of BYD for treating MI in a rat model of left anterior descending coronary artery (LADCA) ligation. The results indicated that BYD has a significantly cardioprotective role against MI by decreasing the infarct size, converting the echocardiographic abnormalities and myocardial enzyme markers, and reversing the serum metabolic disorders and myocardial transcriptional perturbations resulting from MI. Integrated bioinformatics analysis and literature reports constructed the interaction network based on the changes of the key MI targeted-metabolites and transcripts after BYD treatment and disclosed that the cardioprotection of BYD is mainly involved in the regulation of energy homeostasis, oxidative stress, apoptosis, inflammation, cardiac contractile dysfunction, and extracellular matrix remodeling. The results of histopathological examination, quantitative RT-PCR assay, cardiac energy synthesis, and serum antioxidant assessment complemented the multi-omics findings, and indicated the multi-pathway modulation mechanisms of BYD. Our investigation demonstrated that the multi-omics approach could achieve a complementary and verified view for the comprehensive evaluation of therapeutic effects and complex mechanisms of TCMF like BYD.
Establishing and Evaluating Autoverification Rules with Intelligent Guidelines for Arterial Blood Gas Analysis in a Clinical Laboratory

Arterial blood gas (ABG) analysis is important for acutely ill patients and should be performed by qualified laboratorians. The existing manual verifications are tedious, time-consuming, and prone to send wrong reports. Autoverification uses computer-based rules to verify clinical laboratory test results without manual review. To date, no data are available on the use of autoverification for ABG analysis. All autoverification rules were established according to AUTO10-A. Additionally, the rules were established using retrospective patient data, and then validated by actual clinical samples in a “live” environment before go-live. The average autoverification passing rate was 75.5%. The turnaround time (TAT) was reduced by 33.3% (27 min vs 18 min). Moreover, the error rate fell to 0.05% after implementation. Statistical analysis resulted in a kappa statistic of 0.92 (p < 0.01), indicating close agreement between autoverification and senior technician verification, and the chi-square value was 22.4 (p < 0.01), indicating that the autoverification error rate was lower than the manual verification error rate. Results showed that implementing autoverification rules with intelligent guidelines for ABG analysis of patients with critical illnesses could decrease the number of samples requiring manual verification, reduce TAT, and eliminate errors, allowing laboratorians to concentrate more time on abnormal samples, patient care, and collaboration with physicians.
The Pliocene Model Intercomparison Project (PlioMIP) Phase 2: scientific objectives and experimental design

Abstract. The Pliocene Model Intercomparison Project (PlioMIP) is a co-ordinated international climate modelling initiative to study and understand climate and environments of the Late Pliocene, as well as their potential relevance in the context of future climate change. PlioMIP examines the consistency of model predictions in simulating Pliocene climate and their ability to reproduce climate signals preserved by geological climate archives. Here we provide a description of the aim and objectives of the next phase of the model intercomparison project (PlioMIP Phase 2), and we present the experimental design and boundary conditions that will be utilized for climate model experiments in Phase 2. Following on from PlioMIP Phase 1, Phase 2 will continue to be a mechanism for sampling structural uncertainty within climate models. However, Phase 1 demonstrated the requirement to better understand boundary condition uncertainties as well as uncertainty in the methodologies used for data–model comparison. Therefore, our strategy for Phase 2 is to utilize state-of-the-art boundary conditions that have emerged over the last 5 years. These include a new palaeogeographic reconstruction, detailing ocean bathymetry and land–ice surface topography. The ice surface topography is built upon the lessons learned from offline ice sheet modelling studies. Land surface cover has been enhanced by recent additions of Pliocene soils and lakes. Atmospheric reconstructions of palaeo-CO2 are emerging on orbital timescales, and these are also incorporated into PlioMIP Phase 2. New records of surface and sea surface temperature change are being produced that will be more temporally consistent with the boundary conditions and forcings used within models. Finally we have designed a suite of prioritized experiments that tackle issues surrounding the basic understanding of the Pliocene and its relevance in the context of future climate change in a discrete way.
An Approach to Accurate Inversion of Convolution Transforms by FIR Filters

Inversion of convolution transforms is considered by FIR filters for aperiodic bandand time-unlimited signals from the perspective attaining maximum accurate inverted waveforms with controllable noise amplification of the filter . The difficulties hampering to gain this goal, such as a lack of knowledge how the digital filter shall deviate from ideal one to produce waveforms as accurately as possible, complexity to choose optimal sampling rate, necessity to sacrifice the accuracy for suppressing noise, etc. are analysed. Based on learning in the input-output signal domain and controlling noise amplification by varying sampling rate, an approach is developed for designing maximum accurate filters, which are specified only by two user’s relevant parameters: (i) the desired noise gain and (ii) the continuous time support. Implementation of the approach is ill ustrated by designing a digital differentiator for the logarithmic derivative and a digital estimator of the distribution of relaxation times. Simulation results are presented demonstrating that the approach allows constructing more accurate FIR filters with predefined noise amplification and support sizes compared with those designed by other commonly used techniques. Key-Words: Convolution Transform, Inversion, Deconvolution, FIR Filter, Accuracy, Noise Amplification, Design by Learning
Synchronous and Time-Dependent Expression of Cyclins, Cyclin-Dependant Kinases, and Apoptotic Genes in the Rumen Epithelia of Butyrate-Infused Goats

In our previous study, we demonstrated that butyrate induced ruminal epithelial growth through cyclin D1 upregulation. Here, we investigated the influence of butyrate on the expression of genes associated with cell cycle and apoptosis in rumen epithelium. Goats (n = 24) were given an intra ruminal infusion of sodium butyrate at 0.3 (group B, n = 12) or 0 (group A, n = 12) g/kg of body weight (BW) per day before morning feeding for 28 days and were slaughtered (4 goat/group) at 5,7 and 9 h after butyrate infusion. Rumen fluid was analyzed for short chain fatty acids (SCFAs) concentration. Ruminal tissues were analyzed for morpho-histrometry and the expressions of genes associated with cell cycle and apoptosis. The results revealed that the ruminal butyrate concentration increased (P < 0.05) in B compared to group A. Morphometric analysis showed increased (P < 0.05) papillae size associated with higher number of cell layers in epithelial strata in B compared to A. Butyrate-induced papillae enlargement was coupled with enhanced mRNA expression levels (P < 0.05) of cyclin D1, CDK2, CDK4, and CDK6 (G0/G1 phase regulators) at 5 h, cyclin E1 (G1/S phase regulator) at 7 h and cyclin A and CDK1 (S phase regulators) at 9 h post-infusion compared to A group. In addition, the mRNA expression levels of apoptotic genes, i.e., caspase 3, caspase 9 and Bax at 5 h post-infusion were upregulated (P < 0.05) in group B compared to group A. The present study demonstrated that butyrate improved ruminal epithelial growth through concurrent and time-dependent changes in the expressions of genes involved in cell proliferation and apoptosis. It seems that the rate of proliferation was higher than the apoptosis which was reflected in epithelial growth.