Miracle-dz/UniFAR-FTUs huggingface dataset:
Joint Pricing and Decision-Making for Heterogeneous User Demand in Cognitive Radio Networks

The cognitive radio technique allows secondary users (SUs) to share the spectrum with primary users (PUs) in an exclusive or opportunistic manner. This paper studies spectrum pricing conducted by spectrum owners, that is, primary operators (POs), and SU decision-making strategies for three kinds of duopoly markets. The single-band exclusive use market considers two POs with each providing a single band dedicated to SUs. A pre-emptive resume priority (PRP) M/M/1 queueing model is presented, based on which SUs decide to join which PO and which queue. We prove the existence of a unique Wardrop equilibrium for the decision-making process, and a unique Nash equilibrium for the proposed parallel pricing strategy. In a single-band mixed use market, the competition of two POs is represented by a Stackelberg game. We formulate the spectrum sharing among PU and SUs with a 3-level PRP M/M/1 queueing structure, and derive the close form expressions of SUs’ queueing delay. In a multiband exclusive use market, where POs have to determine how many bands they will rent as well as the admission price, we define the problem as a mixed integer linear programming problem and propose a global particle swarm optimization algorithm to find the global optimum. Finally, we study a generalized scenario with multiple POs and multiple priority queues.
Learning predictive models of drug side-effect relationships from distributed representations of literature-derived semantic predications

Objective The aim of this work is to leverage relational information extracted from biomedical literature using a novel synthesis of unsupervised pretraining, representational composition, and supervised machine learning for drug safety monitoring. Methods Using ≈80 million concept-relationship-concept triples extracted from the literature using the SemRep Natural Language Processing system, distributed vector representations (embeddings) were generated for concepts as functions of their relationships utilizing two unsupervised representational approaches. Embeddings for drugs and side effects of interest from two widely used reference standards were then composed to generate embeddings of drug/side-effect pairs, which were used as input for supervised machine learning. This methodology was developed and evaluated using cross-validation strategies and compared to contemporary approaches. To qualitatively assess generalization, models trained on the Observational Medical Outcomes Partnership (OMOP) drug/side-effect reference set were evaluated against a list of ≈1100 drugs from an online database. Results The employed method improved performance over previous approaches. Cross-validation results advance the state of the art (AUC 0.96; F1 0.90 and AUC 0.95; F1 0.84 across the two sets), outperforming methods utilizing literature and/or spontaneous reporting system data. Examination of predictions for unseen drug/side-effect pairs indicates the ability of these methods to generalize, with over tenfold label support enrichment in the top 100 predictions versus the bottom 100 predictions. Discussion and Conclusion Our methods can assist the pharmacovigilance process using information from the biomedical literature. Unsupervised pretraining generates a rich relationship-based representational foundation for machine learning techniques to classify drugs in the context of a putative side effect, given known examples.
Practical Inductive Link Design for Biomedical Wireless Power Transfer: A Tutorial

Wireless power transfer systems, particularly those based on inductive coupling, provide an increasingly attractive method to safely deliver power to biomedical implants. Although there exists a large body of literature describing the design of inductive links, it generally focuses on single aspects of the design process. There is a variety of approaches, some analytic, some numerical, each with benefits and drawbacks. As a result, undertaking a link design can be a difficult task, particularly for a newcomer to the subject. This tutorial paper reviews and collects the methods and equations that are required to design an inductive link for biomedical wireless power transfer, with a focus on practicality. It introduces and explains the published methods and principles relevant to all aspects of inductive link design, such that no specific prior knowledge of inductive link design is required. These methods are also combined into a software package (the Coupled Coil Configurator), to further simplify the design process. This software is demonstrated with a design example, to serve as a practical illustration.
“ What ” — Then — “ Where ” in Visual Working Memory : An Event-Related fMRI Study

Behavioral studies indicate that spatial and object working memory are computed by dissociable subsystems. We investigated the neural bases of this dissociation with a whole-brain fMRI design and analysis technique that permitted direct assessment of delay-period activity, uncontaminated by other components of the trial. The task employed a “what”-then“where” design, with an object and a spatial delay period incorporated in each trial; within-trial order of delay conditions was balanced across each scan. Our experiment failed to and evidence, at the single-subject level and at the group level, for anatomical segregation of spatial and object working memory function in the frontal cortex. Delay-period activity in the caudate nucleus revealed a sensitivity to position in the trial in the spatial, but not the object, condition. In posterior regions, spatial delay-period activity was associated with preferential recruitment of extrastriate areas falling within Brodmann’s area 19 and, less reliably, the superior parietal lobule. Object-speciac delay-period activity was found predominantly in ventral regions of the posterior cortex and demonstrated more topographic variability across subjects than did spatial working
CMOS Luminescence Imager With Ambient Light Compensation and Lifetime to Frequency Conversion

This paper presents a novel <inline-formula><tex-math notation="LaTeX">${\text{32}}\times {\text{64}}$</tex-math> </inline-formula> CMOS image sensor for luminescence imaging with direct lifetime-dependent digital pulse frequency modulated output. Recently reported parasitic insensitive multicycle charge modulation scheme is applied to accumulate photon-generated charges in discrete programmable time windows over multiple exposures. An autoreset pulse serving as the digital output is generated by comparing the multicycle charge integrated output with a reference threshold. The detected luminescence's lifetime is extracted by monitoring the frequency in this digital pulse. To compensate for the background photocurrent generated by ambient light and built-in offset, a charge pump based calibration circuitry is also proposed. Driven by a 10-KHz clock signal with 20-μs pulse width as the integration time window, the proposed circuitry can achieve <inline-formula><tex-math notation="LaTeX">$\text{93 Hz/}(\mu \text{W/cm}^{2})$ </tex-math></inline-formula> responsivity and <inline-formula><tex-math notation="LaTeX">${\text{19 nW/cm}}^{2}$ </tex-math></inline-formula> resolution at 575 nm wavelength. It has lifetime resolution of 8 ns. The proposed sensor chip was applied for lifetime measurement of a Ru(dpp)<sub>3</sub>(PF<sub>6</sub>)<sub>2</sub> fluorescent sample whose lifetime was estimated to be 4.2 μs. A two-dimensional luminescence intensity and lifetime images of a single white LED have also been obtained to further validate its functionality.
Point-cloud registration using adaptive radial basis functions

Abstract Non-rigid registration is a common part of bioengineering model-generation workflows. Compared to common mesh-based methods, radial basis functions can provide more flexible deformation fields due to their meshless nature. We introduce an implementation of RBF non-rigid registration with iterative knot-placement to adaptively reduce registration error. The implementation is validated on surface meshes of the femur, hemi-pelvis, mandible, and lumbar spine. Mean registration surface errors ranged from 0.37 to 0.99 mm, Hausdorff distance from 1.84 to 2.47 mm, and DICE coefficients from 0.97 to 0.99. The implementation is available for use in the free and open-source GIAS2 library.
Acts of Omission, Altered Worldviews, and Psychological Problems Among Military Veterans

Objective: The present study explored acts of omission (i.e., inactions) among military service members. We also investigated whether the meanings and interpretations that service members assign to their actions and inactions, particularly alterations to their conceptualization of themselves, others, and the world (i.e., altered worldviews) would be associated with psychological problems (specifically, depression, suicidality, posttraumatic stress disorder [PTSD], and alcohol use). Method: A sample of 50 Iraq/Afghanistan military veterans (8% female) completed questionnaires measuring their (in)actions and the meanings and interpretations attached to those (in)actions. They also completed questionnaires measuring PTSD, depression, suicidality, alcohol use, and combat/postcombat experience. Results: Higher levels of acts of omission were associated with higher levels of altered worldviews and psychological problems. Altered worldviews were strongly associated with PTSD, depression, and suicidality, even after taking into account age, gender, combat/postcombat experiences, and guilt/shame. Conclusion: Altered worldviews and acts of omission were strongly associated with psychological problems.
Professional occupation and the risk of Parkinson's disease

Creativity in Parkinson's disease (PD) is strongly related to dopaminergic activity and medication. We hypothesized that patients with PD, including those who are in the pre‐diagnostic phase of PD, are prone to choose highly structured ‘conventional’ professional occupations and avoid highly creative ‘artistic’ occupations.
Infants’ Evaluation of Prosocial and Antisocial Agents: A Meta-Analysis

Over the past decade, numerous studies have reported that infants prefer prosocial agents (those who provide help, comfort, or fairness in distributive actions) to antisocial agents (those who harm others or distribute goods unfairly). We meta-analyzed the results of published and unpublished studies on infants aged 4–32 months and estimated that approximately two infants out of three, when given a choice between a prosocial and an antisocial agent, choose the former. This preference was not significantly affected by age or other factors, such as the type of dependent variable (selective reaching or helping) or the modality of stimulus presentation (cartoons or real events). Effect size was affected by the type of familiarization events: giving/taking actions increased its magnitude compared with helping/hindering actions. There was evidence of a publication bias, suggesting that the effect size in published studies is likely to be inflated. Also, the distribution of children who chose the prosocial agent in experiments with N = 16 suggested a file-drawer problem.
Response to Osteoporotic Vertebral Fracture Prevalence Varies Widely

Dear Prof. Civitelli, We thank Dr Gilchrist and colleagues for their letter entitled "Osteoporotic vertebral fracture prevalence varies widely" in which they outline their experience with clinical health ontology applied on a shared repository of clinical notes, radiological images and reports. The purpose of their effort is to "assess whether patients with fractures are receiving appropriate care" and to "streamline the approach to diagnosing and treating those people with vertebral fractures without the use of significant additional resources".
Information Fusion for Human Action Recognition via Biset/Multiset Globality Locality Preserving Canonical Correlation Analysis

In this paper, we study the problem of human action recognition, in which each action is captured by multiple sensors and represented by multisets. We propose two novel information fusion techniques for fusing the information from multisets. The first technique is biset globality locality preserving canonical correlation analysis (BGLPCCA), which aims to learn the common feature subspace between two sets. The second technique is multiset globality locality preserving canonical correlation analysis (MGLPCCA), which aims to deal with three or more sets. The proposed BGLPCCA and MGLPCCA are able to learn a low-dimensional common subspace that preserves the local and global structures of data samples. Moreover, two novel descriptors are presented for both depth and skeleton. We then propose a new human action recognition framework employing the proposed BGLPCCA or MGLPCCA to learn the shared subspace from multiple sets of features including skeleton, depth, and optical flow. Extensive experiments on five publicly available datasets (MSR Action3D, UTD multimodal human action dataset, multimodal action database, Kinect activity recognition dataset, and SBU Kinect interaction dataset) demonstrate the effectiveness of the proposed framework.
Daily variation in the prokaryotic community during a spring bloom in shelf waters of the East China Sea

ABSTRACT To understand prokaryotic responses during a spring bloom in offshore shelf waters, prokaryotic parameters were measured daily at a station located in the middle of the East China Sea over a six-week period from March 25 to May 19. The site experienced a phytoplankton bloom in late April, triggering changes in prokaryotic abundance and production after a lag of approximately one week. Before the bloom, changes in prokaryotic composition were small. Both during the bloom and in the post-bloom period, successive changes among bacterial groups were apparent. A SAR11 group became more dominant during the bloom period, and diverse groups belonging to the Flavobacteriia occurred dominantly during both the bloom and post-bloom periods. However, bacterial community changes at the species level during the bloom and post-bloom periods occurred rapidly in a time scale of a few days. Especially, NS5, NS4 and Formosa bacteria belonging to Flavobacteriia and bacteria belonging to Halieaceae and Arenicellaceae families of Gammaproteobacteria showed a successive pattern with large short-term variation during the period. The changes in prokaryotic composition were found to be related to phytoplankton biomass and composition, as well as seawater temperature and variations in nutrients.
The Impact of Anxiety and Depression on the Outcomes of Chronic Low Back Pain Multidisciplinary Pain Management—A Multicenter Prospective Cohort Study in Pain Clinics with One‐Year Follow‐up

Objective. The psychological health of patients with chronic low back pain (CLBP) influences their response to a number of conservative and invasive pain treatments. However, evidence is still scarce regarding the impact of anxiety and depression in the clinical outcomes of multidisciplinary pain management over time. This study, based on longitudinal data from a clinical practice setting, aimed to assess the effectiveness of the usual multidisciplinary approach provided to CLBP patients and to explore the impact of anxiety and depression symptoms and their interaction on clinical outcomes. Methods. In this study, participants included were adult patients in their first consultation in a multidisciplinary chronic pain clinic. Anxiety and depression symptoms were assessed with the Hospital Anxiety and Depression Scale (HADS). The Brief Pain Inventory (BPI) and the Shortened Treatment Outcomes in Pain Survey (S‐TOPS) were used to assess outcomes. Linear mixed effects models were used to assess the impact of anxiety, depression, and their interaction on treatment outcomes. Results. A total of 284 patients (age 60.4 ± 13.7 years, 74.6% female) with CLBP were included at baseline. The majority of patients had both anxiety and depression and experienced higher pain severity (P < 0.001) and higher pain‐related disability (P < 0.001). Anxiety and depression mainly predicted changes in pain interference over time. Their interaction significantly predicted changes in pain interference. Conclusions. Anxiety, depression, and their interaction are associated with changes in pain disability at one‐year follow‐up. These findings encourage the pretreatment screening of anxiety and depression as independent symptoms in patients with CLBP in order to design more tailored and effective multidisciplinary treatments.
Self-Similarity Constrained Sparse Representation for Hyperspectral Image Super-Resolution

Fusing a low-resolution hyperspectral (HS) image with the corresponding high-resolution multispectral image to obtain a high-resolution HS image is an important technique for capturing comprehensive scene information in both the spatial and spectral domains. Existing approaches adopt sparsity promoting strategy and encode the spectral information of each pixel independently, which results in noisy sparse representation. We propose a novel HS image super-resolution method via a self-similarity constrained sparse representation. We explore the similar patch structures across the whole image and the pixels with close appearance in the local regions to create global-structure groups and local-spectral super-pixels. By forcing the similarity of the sparse representations for pixels belonging to the same group and super-pixel, we alleviate the effect of the outliers in the learned sparse coding. Experiment results on benchmark datasets validate that the proposed method outperforms the state-of-the-art methods in both the quantitative metrics and visual effect.
Adaptive Voting Rules for k-Nearest Neighbors Classifiers

A simple form of cooperation between the k-nearest neighbors (NN) approach to classification and the neural-like property of adaptation is explored. A tunable, high level k-nearest neighbors decision rule is defined that comprehends most previous generalizations of the common majority rule. A learning procedure is developed that applies to this rule and exploits those statistical features that can be induced from the training set. The overall approach is tested on a problem of handwritten character recognition. Experiments show that adaptivity in the decision rule may improve the recognition and rejection capability of standard k-NN classifiers.
Using automated electrode localization to guide stimulation management in DBS

Deep Brain Stimulation requires extensive postoperative testing of stimulation parameters to achieve optimal outcomes. Testing is typically not guided by neuroanatomical information on electrode contact locations. To address this, we present an automated reconstruction of electrode locations relative to the treatment target, the subthalamic nucleus, comparing different targeting methods: atlas‐, manual‐, or tractography‐based subthalamic nucleus segmentation. We found that most electrode contacts chosen to deliver stimulation were closest or second closest to the atlas‐based subthalamic nucleus target. We suggest that information on each electrode contact's location, which can be obtained using atlas‐based methods, might guide clinicians during postoperative stimulation testing.
Review and in silico analysis of fermentation, bioenergy, fiber, and biopolymer genes of biotechnological interest in Agave L. for genetic improvement and biocatalysis

Several of the over 200 known species of Agave L. are currently used for production of distilled beverages and biopolymers. The plants live in a wide range of stressful environments as a result of their resistance to abiotic stress (drought, salinity, and extreme temperature) and pathogens, which gives the genus potential for germplasm conservation and biotechnological applications that may minimize economic losses as a result of the global climate change. However, the limited knowledge in the genus of genome structure and organization hampers development of potential improved biotechnological applications by means of genetic manipulation and biocatalysis. We reviewed Agave and plant sequences in the GenBank NCBI database for identifying genes with biotechnological potential for fermentation, bioenergy, fiber improvement, and in vivo plant biopolymer production. Three‐dimensional modeling of enzyme structures in plant accessions revealed structural differences in sucrose 1‐fructosyltransferase, fructan 1‐fructosyltransferase, fructan exohydrolase (1‐FEH), cellulose synthase (CES), and glucanases (EGases) with possible effects in fructan, sugar, and biopolymer production. Although the coding genes of FEH and enzymes involved in biopolymer production (CES, sucrose synthase, and EGases) remain unidentified in Agave L. , our results could aid isolation of such genes in Agave. By comparing nucleotide and amino acid sequences in accessions of Agave and other plants, knowledge may be gained about transcriptional regulation and enzymatic activity factors. Future study is needed of biotechnological application of Agave genes for crop breeding aided by genetic engineering and biocatalysis. © 2018 American Institute of Chemical Engineers Biotechnol. Prog. , 34:1314–1334, 2018
Physical activity and all-cause mortality in Korean older adults

Abstract Background: The association between physical activity (PA) and all-cause mortality may be modulated by potential confounders. Aim: To investigate the association between weekly PA and all-cause mortality in a population-based prospective study. Subjects and methods: The study sample included Korean older adults aged 60 years and older who participated in baseline assessments (n = 15 416) in 2008 and completed follow-up visits in 2011 (n = 14,976). Primary outcome was 3-year all-cause mortality. Results: Compared with sufficiently active individuals (with Hazard Ratio (HR) = 1), completely inactive and insufficiently active individuals had a significantly higher risk of all-cause mortality (HR = 2.086, 95% CI = 1.639–2.655, p < 0.00 and HR = 1.644, 95% CI = 1.013–2.668, p = 0.044, respectively), even after adjustments for age and sex, health-related behaviour factors (i.e. smoking, alcohol intake and nutritional risk), cognitive impairment and components of frailty phenotype (i.e. involuntary weight loss, exhaustion and slowness). In addition, the inverse association between PA and all-cause mortality is differently modulated by potential confounders, including age, sex, smoking, depressive symptoms, cognitive impairment and involuntary weight loss. Conclusion: PA was inversely and independently associated with all-cause mortality in Korean older adults.