Miracle-dz/UniFAR-FTUs huggingface dataset:
Intrinsic analysis for dual word embedding space models

Recent word embeddings techniques represent words in a continuous vector space, moving away from the atomic and sparse representations of the past. Each such technique can further create multiple varieties of embeddings based on different settings of hyper-parameters like embedding dimension size, context window size and training method. One additional variety appears when we especially consider the Dual embedding space techniques which generate not one but two-word embeddings as output. This gives rise to an interesting question - "is there one or a combination of the two word embeddings variety, which works better for a specific task? ". This paper tries to answer this question by considering all of these variations. Herein, we compare two classical embedding methods belonging to two different methodologies - Word2Vec from window-based and Glove from count-based. For an extensive evaluation after considering all variations, a total of 84 different models were compared against semantic, association and analogy evaluations tasks which are made up of 9 open-source linguistics datasets. The final Word2vec reports showcase the preference of non-default model for 2 out of 3 tasks. In case of Glove, non-default models outperform in all 3 evaluation tasks.
Accelerating Bandwidth-Bound Deep Learning Inference with Main-Memory Accelerators

Matrix-matrix multiplication operations (GEMMs) are important in many HPC and machine-learning applications. They are often mapped to discrete accelerators (e.g., GPUs) to improve performance. However, we find that large tall/skinny and fat/short matrices benefit little from discrete acceleration and also do not perform well on a CPU. Such matrices are prevalent in important workloads, such as deep-learning inference within large-scale datacenters. We demonstrate the large potential of accelerating these GEMMs with processing in the main CPU memory, where processing in memory units (PIMs) take advantage of otherwise untapped bandwidth without requiring data copies. We develop a novel GEMM execution flow and corresponding memory-side address-generation logic that exploits GEMM locality and enables long-running PIM kernels despite the complex address-mapping functions employed by the CPU. Our evaluation of StepS tone variants at the channel, device, and within-device PIM levels demonstrate 12x better minimum latency than a CPU and 2.8x greater throughput for strict query latency constraints. End-to-end performance analysis of recent recommendation and language models shows that StepStone outperforms a fast CPU by up to 16x and also the best prior main-memory acceleration approaches by up to 2.4×.
Counting distributions from the perspective of combinants

We present a comprehensive insight into counting distributions from the perspective of the combinants extracted from them. In particular, we focus on cases where these combinants exhibit oscillatory behavior that can provide an invaluable new source of information about the dynamics of the process under study. We show that such behavior can be described only by specific combinations of compound distributions based on the Binomial Distribution and provide their analytical forms which can be used in further investigations and which can be helpful in the analysis of all other types of counting distributions.
NMR Spectroscopy: Basic Principles, Concepts and Applications in Chemistry

The Physical Basis of the Nuclear Magnetic Resonance Experiment Part I. The Proton Magnetic Resonance Spectra of Organic Molecules. Experimental Aspects of Nuclear Magnetic Resonance Spectroscopy. Chemical Shift and Spin-Spin Coupling as Functions of Structure. The Analysis of High-Resolution Nuclear Magnetic Resonance Spectra. The Influence of Molecular Symmetry and Chirality on Proton Magnetic Resonance Spectra. The Physical Basis of the Nuclear Magnetic Resonance Experiment Part II: Fourier Transform and Pulse Nuclear Magnetic Resonance. Two-Dimensional Nuclear Magnetic Resonance Spectroscopy. The Influence of Dynamic Effects on 1H Nuclear Magnetic Resonance Spectra. Selected Experimental Techniques of Nuclear Magnetic Resonance Spectroscopy. Carbon-13 Nuclear Magnetic Resosnance Spectroscopy. Appendix. Bibliography. Solutions to Exercises. Index.
Decentralized Approximate Newton Methods for Convex Optimization on Networked Systems

In this article, a class of decentralized approximate Newton (DEAN) methods for addressing convex optimization on a networked system is developed, where nodes in the networked system seek a consensus that minimizes the sum of their individual objective functions through local interactions only. The proposed DEAN algorithms allow each node to repeatedly perform a local approximate Newton update, which leverages tracking the global Newton direction and dissipating the discrepancies among the nodes. Under less restrictive problem assumptions in comparison with most existing second-order methods, the DEAN algorithms enable the nodes to reach a consensus that can be arbitrarily close to the optimum. Moreover, for a particular DEAN algorithm, the nodes linearly converge to a common suboptimal solution with an explicit error bound. Finally, simulations demonstrate the competitive performance of DEAN in convergence speed, accuracy, and efficiency.
Banach Space Representer Theorems for Neural Networks and Ridge Splines

We develop a variational framework to understand the properties of the functions learned by neural networks fit to data. We propose and study a family of continuous-domain linear inverse problems with total variation-like regularization in the Radon domain subject to data fitting constraints. We derive a representer theorem showing that finite-width, single-hidden layer neural networks are solutions to these inverse problems. We draw on many techniques from variational spline theory and so we propose the notion of polynomial ridge splines, which correspond to a single-hidden layer neural networks with truncated power functions as the activation function. The representer theorem is reminiscent of the classical reproducing kernel Hilbert space representer theorem, but we show that the neural network problem is posed over a non-Hilbertian Banach space. While the learning problems are posed in the continuous-domain, similar to kernel methods, the problems can be recast as finite-dimensional neural network training problems. These neural network training problems have regularizers which are related to the well-known weight decay and path-norm regularizers. Thus, our result gives insight into functional characteristics of trained neural networks and also into the design neural network regularizers. We also show that these regularizers promote neural network solutions with desirable generalization properties.
Synthetic Kramers Pair in Phononic Elastic Plates and Helical Edge States on a Dislocation Interface

In conventional theories, topological band properties are intrinsic characteristics of the bulk material and do not depend on the choice of the reference frame. In this scenario, the principle of bulk‐edge correspondence can be used to predict the existence of edge states between topologically distinct materials. In this study, a 2D elastic phononic plate is proposed with a Kekulé‐distorted honeycomb pattern engraved on it. It is found that the pseudospin and the pseudospin‐dependent Chern numbers are not invariant properties, and the ℤ2 number is no longer a sufficient indicator to examine the existence of the edge state. The distinctive pseudospin texture and the pseudomagnetic field are also revealed. Finally, the synthetic helical edge states are successfully devised and experimentally implemented on a dislocation interface connecting two subdomains with bulk pattern identical up to a relative translation. The edge state is also imaged via laser vibrometry.
The Impact of Vasopressor and Sedative Agents on Cerebrovascular Reactivity and Compensatory Reserve in Traumatic Brain Injury: An Exploratory Analysis

The impact of vasopressor and sedative drugs on cerebrovascular reactivity in traumatic brain injury (TBI) remains unclear. The aim of this study was to evaluate the impact of changes of doses of commonly administered sedation (i.e., propofol, fentanyl, and ketamine) and vasopressor agents (i.e., norepinephrine [NE], phenylephrine [PE], and vasopressin[VSP]) on cerebrovascular reactivity and compensatory reserve in patients with moderate/severe TBI. Using the Winnipeg Acute TBI Database, we identified 38 patients with more than 1000 distinct changes of infusion rates and more than 500 h of paired drug infusion/physiology data. Cerebrovascular reactivity was assessed using pressure reactivity index (PRx) and cerebral compensatory reserve was assessed using RAP (the correlation [R] between pulse amplitude of intracranial pressure [ICP; A] and ICP [P]). We evaluated the data in two phases. First, we assessed the relationship between mean hourly dose of medication and its relation to both mean hourly index values, and time spent above a given index threshold. Second, we evaluated time-series data for each individual dose change per medication, assessing for a statistically significant change in PRx and RAP metrics. The results of the analysis confirmed that, overall, the mean hourly dose of sedative (propofol, fentanyl, and ketamine) and vasopressor (NE, PE, and VSP) agents does not impact hourly cerebrovascular reactivity or compensatory reserve measures. Similarly, incremental dose changes in these medications in general do not lead to significant changes in cerebrovascular reactivity or compensatory reserve. For propofol with incremental dose increases, in situations where PRx is intact (i.e., PRx <0 prior), a statistically significant increase in PRx was seen. However, this may not indicate deteriorating cerebrovascular reactivity as the final PRx (∼0.05) may still be considered to be intact cerebrovascular reactivity. As such, this finding with regards to propofol remains “weak. ” This study indicates that commonly administered sedative and vasopressor agents with incremental dosing changes have no clinically significant influence on cerebrovascular reactivity or compensatory reserve in TBI. These results should be considered preliminary, requiring further investigation.
Application of Hydrodynamic Cavitation in Environmental Engineering

About the author List of symbols Introduction CHAPTER 1: Characteristics of the cavitation phenomenon 1.1 The essence of cavitation 1.2 Types of cavitation-forms of cavitation clouds 1.3 Factors favouring the formation of cavitation 1.4 Physicochemical effects of the cavitation process 1.5 Summary CHAPTER 2: The physical basics of hydrodynamic cavitation 2.1 Types of cavitation liquids. Basic classification 2.2 Phase transition characteristics of water 2.3 The solubility of selected gases in water 2.4 The thermodynamic model of hydrodynamic cavitation 2.4.1 The thermodynamic model for the liquid-vapour transformation at the phase transition interface 2.4.2 The cavitation bubble dynamics model 2.4.3 Static equilibrium in a gas bubble 2.5 Cavitation bubble oscillations and implosions 2.6 Cavitation number CHAPTER 3: Sonochemical processes in support of oxidation processes 3.1 Advanced oxidation processes 3.2 The mechanism and kinetics of reactions involving hydroxyl radicals 3.3 Cavitation characteristics with the participation of ultrasound 3.4 Sonochemical reactions under the influence of ultrasound 3.5 Summary CHAPTER 4: Problems and conditions in the generation of hydrodynamic cavitation 4.1 Parameters affecting cavitation intensity 4.2 Cavitation device classification 4.3 Hydrodynamic cavitation reactor selection criteria CHAPTER 5: The study of hydrodynamic cavitation in the laboratory 5.1 Introduction 5.2 The characteristics and description of the research facility 5.2.1 The research facility 5.2.2 The hydrodynamic cavitation reactor 5.3 The effect of certain parameters on the cavitation intensity 5.3.1 The shape of the cavitation inducer 5.3.2 Pressure variations in the cavitation region CHAPTER 6: The use of cavitation to aid the water treatment process and effluent decontamination 6.1 Introduction 6.2 Water treatment and disinfection 6.3 Sewage treatment 6.4 Cleaning leachate from municipal landfills 6.5 Sludge digestion 6.6 The degradation of organic compounds in aqueous solutions 6.7 Summary CHAPTER 7: The decomposition of persistent organic pollutants using hydrodynamic cavitation 7.1 Introduction 7.2 The decomposition of PAHs in aqueous solutions 7.3 The reduction of odour emissions from counter-current extraction water in the sugar industry 7.4 Summary CHAPTER 8: The application of cavitation to intensify technological processes 8.1 Introduction 8.2 The use of cavitation in the food and processing industries 8.3 Chemical synthesis 8.3.1 The hydrolysis of vegetable oils 8.3.2 The synthesis of biodiesel 8.4 The application of cavitation in environmental decontamination processes 8.4.1 Using cavitation to treat wastewater during mining 8.4.2 Cavitation and flotation 8.4.3 Using cavitation to aerate natural waters 8.5 Using cavitation in the treatment of ballast water 8.6 Cavitation in the disposal of petroleum products 8.7 Summary CHAPTER 9: Application opportunities for hydrodynamic cavitation in environmental engineering technologies Subject index
Effect of Elevated Ketone Body on Maternal and Infant Outcome of Pregnant Women with Abnormal Glucose Metabolism During Pregnancy

Abstract Ketone bodies are one of the products of fat metabolism which can be used as an alternative energy source for the human body in states of glucose deficiency. Normal pregnant women may develop ketosis due to physiological changes during pregnancy, while pregnant women with abnormal glucose metabolism are more likely to develop ketosis due to abnormal insulin secretion. Animal experiments and clinical studies have shown that exposure to high-ketone environments during pregnancy is closely related to adverse maternal and infant outcomes. However, there is no unified conclusion on whether ketone bodies should be routinely monitored during pregnancy. This review summarizes the existing studies on ketone body levels and pregnancy outcomes in the case of abnormal blood glucose during pregnancy, elaborates the current guidelines on the level of ketone bodies, provides the detection and treatment of ketosis in pregnant women with abnormal blood glucose in the clinical practice.
Hippocampal Neural Stem Cell Grafting after Status Epilepticus Alleviates Chronic Epilepsy and Abnormal Plasticity, and Maintains Better Memory and Mood Function

Hippocampal damage after status epilepticus (SE) leads to multiple epileptogenic changes, which lead to chronic temporal lobe epilepsy (TLE). Morbidities such as spontaneous recurrent seizures (SRS) and memory and mood impairments are seen in a significant fraction of SE survivors despite the administration of antiepileptic drugs after SE. We examined the efficacy of bilateral intra-hippocampal grafting of neural stem/progenitor cells (NSCs) derived from the embryonic day 19 rat hippocampi, six days after SE for restraining SE-induced SRS, memory, and mood impairments in the chronic phase. Grafting of NSCs curtailed the progression of SRS at 3-5 months post-SE and reduced the frequency and severity of SRS activity when examined at eight months post-SE. Reduced SRS activity was also associated with improved memory function. Graft-derived cells migrated into different hippocampal cell layers, differentiated into GABA-ergic interneurons, astrocytes, and oligodendrocytes. Significant percentages of graft-derived cells also expressed beneficial neurotrophic factors such as the fibroblast growth factor-2, brain-derived neurotrophic factor, insulin-like growth factor-1 and glial cell line-derived neurotrophic factor. NSC grafting protected neuropeptide Y- and parvalbumin-positive host interneurons, diminished the abnormal migration of newly born neurons, and rescued the reelin+ interneurons in the dentate gyrus. Besides, grafting led to the maintenance of a higher level of normal neurogenesis in the chronic phase after SE and diminished aberrant mossy fiber sprouting in the dentate gyrus. Thus, intrahippocampal grafting of hippocampal NSCs shortly after SE considerably curbed the progression of epileptogenic processes and SRS, which eventually resulted in less severe chronic epilepsy devoid of significant cognitive and mood impairments.
Incidence and Survival for Common Cancers Are Lower in New Mexico and Along the US-Mexico Border Than Elsewhere in the United States

Background Few in-depth reports on cancer epidemiology in New Mexico or the United States-Mexico border region exist. We aim to quantify cancer incidence and survival in New Mexico and the United States-Mexico border region in New Mexico. Methods Incidence and survival were obtained using SEER*Stat 8.3. The data were divided into either New Mexico, or SEER 18 (comprised of the 17 remaining regions) and then further divided by county in New Mexico and by time period. Incidence rates were age-standardized to the 2000 US census. Five-year survival was calculated for each cancer type. Kaplan-Meier survival plots were produced, and significance was determined using log-rank analysis. Results Analysis demonstrated that cancers in New Mexico are diagnosed at a lower rate with the exception of thyroid, liver, and ovarian. Survival is generally lower in New Mexico with 10 of the 14 cancers having worse survival in New Mexico. Only uterine cancer had improved survival in New Mexico (77.9% vs 74.9%, P < .001). Additionally, breast (82.2%), prostate (83.3%), lung and bronchus (13.7%), colorectal (53.7%), melanoma (80.1%), kidney and renal pelvis (61.2%), uterine (78.5%), and ovarian (41.6%) all had lower survival in the border counties. Conclusion Comparing New Mexico to the other regions in the SEER 18 database, both cancer incidence and survival are consistently lower; these findings could be explained by lower access to healthcare, which can result in underreporting and delays in diagnosis.
Co-Occurrence of Systemic Lupus Erythematosus and Autoimmune Polyendocrine Syndrome II: Is There a Pathologic Link?

Autoimmune polyendocrine syndrome type II (APS II) is a rare endocrine disorder that involves the adrenal gland (Addison’s disease), thyroid (autoimmune thyroiditis), pancreas (type 1 diabetes), and other non-endocrine organs. Herein, we report a case of a 58-year-old woman with a past medical history of systemic lupus erythematosus (SLE) and Addison’s disease, who initially presented with nocturia, polyuria, abnormal sweating, fatigue, hair thinning, heat and cold intolerance, and progressive darkening of the skin for the last few months. After a thorough evaluation, she was diagnosed with autoimmune thyroiditis, and thus, she met the criteria for APS II. This report highlights the unusual presentation of APS II in a patient with SLE. We also discuss common pathophysiological mechanisms that can explain the concurrence of SLE and APS II in this patient.
Preoperative Immune Prognostic Index Can Predict the Clinical Outcomes of Patients with Gallbladder Cancer: Single-Center Experience

Purpose The immune prognostic index (IPI) has been used as a prognostic biomarker in various cancers. However, the prognostic value of the IPI in gallbladder cancer remains to be determined. Patients and Methods This study included 139 patients who were diagnosed with gallbladder cancer after surgical resection from 2003 to 2017. We used a Kaplan–Meier curve analysis to evaluate the overall survival (OS). Cox proportional hazards regression methodology was used to identify significant independent prognostic factors. Prognostic nomograms for predicting OS were established to achieve superior discriminatory abilities. The prognostic nomograms were verified according to the concordance index, calibration curves, and decision curve analyses in the training cohort and validation cohort. Results Of all 139 patients, 87 (62.6%) patients accepted R0 resection, 32% and 68% were stratiﬁed into the good and poor IPI group, respectively. The median OS was 55.9 (range, 5.93–182.7) months in the good IPI group and 15.47 (range, 0.29–190.37) months in the poor IPI group (P < 0.001). In the multivariate Cox model, the IPI was an independent predictor of OS along with the CA19-9, curative resection, and postoperative chemoradiotherapy. A nomogram based on these factors was efficient in predicting 1-, 3-, and 5-year survival probabilities. The nomogram showed higher sensitivity and specificity than the current cancer TNM staging system in the training cohort and validation cohort. Conclusion The IPI is an independent prognostic factor in gallbladder cancer. Our IPI-based nomogram can serve as a useful and convenient prognostic tool for gallbladder cancer.
Levels of Carbohydrate Antigen 125 in Patients With Adult Onset Still Disease: A Case Report

Adult onset Still disease (AoSD) is a rare systemic polygenic non-familial autoinflammatory disease. There is no specific biological parameter for diagnosis of AoSD today. This paper presents a case series of three patients with AoSD who had elevated baseline levels of carbohydrate antigen 125 (CA 125). The clinical course of patients was favorable with treatment modalities including steroids and non-steroidal anti-inflammatory drugs. After a comprehensive literature search, it appears that this is the first paper on the association between AoSD and CA 125.
Alteration of Metabolic Profile and Potential Biomarkers in the Plasma of Alzheimer’s Disease

The expending of elderly population worldwide leads to a dramatical rising in the incidence of chronic diseases including Alzheimer’s Disease (AD) in the elderly. The inadequate understanding of the mechanisms underlying AD is deemed the greatest stumbling block against progress in definitive diagnosis and curative intervention of this disease. Efforts have been made towards the discovery of reliable AD biomarkers, but they are either invasive based on neuropathological markers in cerebrospinal fluid (CSF) or expensive using emission tomography scanning or magnetic resonance imaging techniques. With the emergence of high‐throughput technology that could detect and catalogue larger numbers of small metabolites, metabolomics offers hope for a better understanding of AD and subsequent identification of biomarkers.