Miracle-dz/UniFAR-FTUs huggingface dataset:
Fair allocation and linear programming

The purpose of this lecture is to illustrate the versatility of linear programming, and show one way of rounding fractional solutions of linear programs into integral solutions. This rounding procedure is referred to as faithful implementation, and we present an application of it in the context of fair allocation of indivisible goods. The manuscript Best-ofBoth-Worlds Fair-Share Allocations by Babaioff, Ezra, and Feige [2021] contains the relevant material for this topic (and more). For convenience of the students in the reading course, we present here (almost verbatim) the portions of that manuscript that are most relevant, and expand on them in some places.
Exploring the Privacy Concerns of Bystanders in Smart Homes from the Perspectives of Both Owners and Bystanders

Smart home IoT devices collect data not only from owners of the devices, but also from bystanders in a smart home (e.g., visiting family members, friends, or domestic workers). Existing research mainly considered the privacy concerns of bystanders from their own perspectives. In this paper, we design and conduct a survey study to more comprehensively explore the privacy concerns of bystanders from the perspectives of both owners and bystanders. For owners, we investigate their understanding of their own data practices, their views on bystanders’ privacy, and their willingness to negotiate data practices with bystanders. For bystanders, we investigate their privacy concerns, their expectations of disclosures by owners, and their willingness to share their data with owners. We recruited 200 owners and 100 bystanders. We found that most owners of smart homes recognize the privacy rights of bystanders, do not fully understand their own data practices, and are willing to address the privacy concerns of trusted bystanders. We also found that most bystanders have concerns about their privacy in other people’s smart homes, do not expect owners to disclose data practices, and are willing to share data about them with owners if they consent. Reaching a temporary agreement about data practices between owners and bystanders might require some negotiation. So, we also explore the willingness of owners and bystanders on negotiating data collection, storage, and sharing in smart homes. We found that many owners and bystanders have different preferences regarding negotiating data practices. Based on our findings, we provide recommendations for enhancing the privacy protection in smart homes.
Systematic review on reducing missed opportunities for vaccinations in Latin America

ABSTRACT Objectives. To estimate the prevalence of missed opportunities for vaccination (MOV) in Latin America and the effect of interventions targeting health systems, health workers, patients, and communities on MOV. Methods. Searches were conducted in MEDLINE, EMBASE, CINAHL, and LILACS electronic databases and relevant organizations were contacted, including the Pan American Health Organization (PAHO), to identify studies meeting eligibility criteria. A pair of reviewers identified 27 randomized and non-randomized studies quantifying the effectiveness of any intervention for reducing MOV and 5 studies assessing the rate of MOV in Latin America. Results are reported narratively when criteria to pool results were not met, and the certainty of this evidence was assessed using the GRADE approach. Results. Evidence suggests the rate of MOV in Latin America ranged from 5% to 37% with a pooled estimate of 17% (95% CI [9, 32]) (low certainty) and that monetary incentives to healthcare teams, training for healthcare teams on how to communicate with patients, and educational interventions for caregivers probably reduce MOV (moderate to very low certainty). Conclusions. There is insufficient evidence supporting the implementation of any intervention as policy based only on the potential reduction of MOV without considering several factors, including costs, feasibility, acceptability, and equity.
Frequency Domain Equalization with Multiple Receiving Antennas for Single Carrier Signaling

ABSTRACT This paper presents a space-time (single-input and multipleoutput (SIMO)) transceiver scheme for reliable transmis-sions over frequency selective fading channels using conven-tional single-carrier M-ary PSK or QAM modulations. Themain feature of this scheme is in appending to the trans-mitted signaling frame a circular sux segment so that byexploiting the spectral structure of this kind of signaling theinter-symbol interference (ISI) e ects could be fully miti-gated at the receiver using ecient processing. It is demon-strated through Monte-Carlo simulations that the perfor-mance of this scheme over time-dispersive channels is com-parable to that of SIMO-OFDM. OFDM has high peak toaverage power ratio (PAPR) and demands the use of highlylinear power ampli ers (PA’s). The proposed scheme o ersthe advantage of reduced constraints on the PA linearityand signaling synchronization, which is critical in wirelessapplications. Categories and Subject Descriptors B.4 [Input/Output and Data Communications]: DataCommunications Devices; C.2. 1 [Network Architectureand Design]: Wireless communication
Design and Analysis of Extendable Switched-Inductor and Capacitor-Divider Network Based High-Boost DC-DC Converter for Solar PV Application

In presented article, an extendable non-isolated high boost converter based on switched-inductor and capacitor-divided (SLCD) network is designed. The high gain, single switch, continuous input current and common ground structure makes it suitable for solar PV applications. The voltage stress across the semiconductor devices is less than the output voltage thus enhancing the efficiency of the converter. The operation in continuous and discontinuous mode of the converter with precise design parameters is presented. A meticulous analysis of voltage gain and efficiency is presented considering the inbuilt resistances of the components and the small-signal model developed evince the stability of the SLCD converter. The proffered converter is weighed against other recent congruent topologies. The theoretical analysis is supported by an experimental set-up of 150W prototype.
Sparse Local Fisher Discriminant Analysis for Gas-Water Two-Phase Flow Status Monitoring With Multisensor Signals

Gas-water two-phase flow has typically stable flow statuses and constantly changing transition flow statuses. Accurate identification and real-time monitoring of flow status are conducive to the in-depth study of two-phase flow and the safe operation of industrial process. A monitoring strategy based on sparse local Fisher discriminant analysis (SLFDA) is proposed in this article. First, multisensor signals are obtained to reflect flow process information. Second, the least absolute shrinkage and selection operator is used to find the sparse discriminant directions to determine the key variables relevant to the flow process from multiple sensor signals. Then, the weight coefficient matrixes of SLFDA keep the original structure of the same flow status data and make the data of different flow statuses more separated, which distinguish different flow statuses to the maximum extent. Finally, two monitoring indexes including the discriminant index and the stability index are established to analyze the dynamic flow process, which enable a concurrent monitoring of both flow evolution and instability to realize fine-scale description of flow process. SLFDA can monitor various flow statuses through only one projection discriminant matrix by transforming high-dimensional signals into features representing the flow characteristics, which avoids model traversal and improves monitoring efficiency. Further study of flow status features provides meaningful physical interpretation and in-depth process analysis with consideration of actual flow process. The application on the data of gas-water two-phase flow in horizontal pipe demonstrates the feasibility and efficacy of the method.
Configurable Hybrid Energy Synchronous Extraction Interface With Serial Stack Resonance for Multi-Source Energy Harvesting

Conventional multi-source energy harvesters use the time-division multiplexing (TDM) scheme, where the inductor operates in discontinuous current mode (DCM) and fails to perform well in continuous current mode (CCM). This article presents a single-inductor hybrid energy synchronous extraction circuit with serial stack resonance (SSR) for multi-source energy harvesting. The proposed circuit incorporates a synchronous electric charge extraction (SECE) circuit for ac energy and two buck–boost circuits for dc energy with a single inductor, which can operate either in a TDM mode to harvest energy from different sources separately or in an SSR mode to extract energy from multiple sources synchronously. The proposed harvester is fabricated in a 0.18- $\mu \text{m}$ CMOS process. It is configured with a photovoltaic (PV) cell, a thermoelectric generator (TEG), and two piezoelectric transducers (PZTs), where the number of PZTs is flexible to meet different application needs.
Control of STING Agonistic/Antagonistic Activity Using Amine-Skeleton-Based c-di-GMP Analogues

Stimulator of Interferon Genes (STING) is a type of endoplasmic reticulum (ER)-membrane receptor. STING is activated by a ligand binding, which leads to an enhancement of the immune-system response. Therefore, a STING ligand can be used to regulate the immune system in therapeutic strategies. However, the natural (or native) STING ligand, cyclic-di-nucleotide (CDN), is unsuitable for pharmaceutical use because of its susceptibility to degradation by enzymes and its low cell-membrane permeability. In this study, we designed and synthesized CDN derivatives by replacing the sugar-phosphodiester moiety, which is responsible for various problems of natural CDNs, with an amine skeleton. As a result, we identified novel STING ligands that activate or inhibit STING. The cyclic ligand 7, with a cyclic amine structure containing two guanines, was found to have agonistic activity, whereas the linear ligand 12 showed antagonistic activity. In addition, these synthetic ligands were more chemically stable than the natural ligands.
Optimal Leader-Following Consensus Control of Multi-Agent Systems: A Neural Network Based Graphical Game Approach

In this article, the optimal leader-following consensus control problem of multi-agent systems is solved using a novel neural network-based (NN-based) integrated heuristic dynamic programming (IHDP) algorithm under a distributed learning framework. The optimal controller is designed to find a Nash equilibrium of the multi-agent differential graphical game. According to the principle of optimality, this problem can be transformed into solving a set of coupled Hamilton-Jacobi-Bellman (HJB) equations, which are difficult to solve directly because of the nonlinearity and strong coupling of the equations. The proposed algorithm combines policy iteration (PI) and value iteration (VI), and the Nash equilibrium of performance index among agents is achieved distributedly, i.e., all agents update their control inputs only use local information. The convergence of the algorithm is rigorously proved. Neural network (NN) approximation implementation is given for the unknown structures of local value functions of agents. The effectiveness of the algorithm is verified by numerical simulation.
Explainable Discrete Collaborative Filtering

Using hashing to learn the binary codes of users and items significantly improves the efficiency and reduces the space consumption of the recommender system. However, existing hashing-based recommender systems remain black boxes without any explainable outputs that illustrate why the system recommends the items. In this paper, we present a new end-to-end discrete recommendation framework based on the multi-task learning to simultaneously perform explainable and efficient recommendation. Toward this goal, an Explainable Discrete Collaborative Filtering (EDCF) method is proposed to preserve the user-item interaction features and semantic text features into binary hash codes by adaptively exploiting the correlations between the preference prediction task and the explanation generation task. At the online recommendation stage, EDCF makes efficient top-K recommendation by calculating the Hamming distances between the feature hash codes, and simultaneously generates natural language explanations for recommendation results through the explanation generation module. To obtain the hash codes directly from the end-to-end neural network, we introduce an attentive TextCNN and an Adaptive Tanh layer in the preference prediction task. For explanation generation, Long Short-Term Memory is employed to generate the explanations for recommendation results from the binary hash codes of user and item. Experiments demonstrate the superiority of the proposed method.
Action Potential Parameters and Spiking Behavior of Cortical Neurons: A Statistical Analysis for Designing Spiking Neural Networks

Cortical neurons exhibit several spiking dynamics both in in-vivo and in-vitro experiments. Neural spikes or action potentials (APs) are also observed in various shapes and forms. Statistical correlation between AP parameters and associated spiking behavior of a neuron is discussed in this article. Three fundamental parameters: 1) width; 2) height; and 3) energy of an AP along with spiking frequency and interspike interval (ISI) are extracted for 91 human cortical neurons selected from Allen Institute for Brain Science (AIBS) database. It has been shown that neurons firing narrow, short, and low-energy APs have higher spiking frequency compared to the neurons with wide and taller APs. For a rise in excitation, it has been presented that information gain for neurons firing wider spikes is less compared to information gain for neurons firing narrow spikes. It has been shown that neurons with low spiking frequency and high spiking frequency dissipate energy of similar order for total spiking activity for similar excitation. Implications of the statistical inferences drawn are explained for a computational model of a spiking neuron. The effect of changing AP width on the overall dynamics of a spiking neural network is also highlighted. The key findings of this study will be useful for designing spiking neural networks for various cognitive applications.
Morphological changes in the cervical muscles of women with chronic whiplash can be modified with exercise—A pilot study

Introduction: In this preliminary study we determined whether MRI markers of cervical muscle degeneration [elevated muscle fatty infiltration (MFI), cross‐sectional area (CSA), and reduced relative muscle CSA (rmCSA)] could be modified with exercise in patients with chronic whiplash. Methods: Five women with chronic whiplash undertook 10 weeks of neck exercise. MRI measures of the cervical multifidus (posterior) and longus capitus/colli (anterior) muscles, neck muscle strength, and self‐reported neck disability were recorded at baseline and at completion of the exercise program. Results: Overall significant increases in CSA and rmCSA were observed for both muscles, but significant reductions in MFI were only evident in the cervical multifidus muscle. These changes coincided with increased muscle strength and reduced neck disability. Conclusions: MRI markers of muscle morphology in individuals with chronic whiplash appear to be modifiable with exercise. Muscle Nerve 52: 772–779, 2015
Metabolomic and Transcriptomic Profiling Identified Significant Genes in Thymic Epithelial Tumor

Thymomas and thymic carcinomas are malignant thymic epithelial tumors (TETs) with poor outcomes if non-resectable. However, the tumorigenesis, especially the metabolic mechanisms involved, is poorly studied. Untargeted metabolomics analysis was utilized to screen for differential metabolic profiles between thymic cancerous tissues and adjunct noncancerous tissues. Combined with transcriptomic data, we comprehensively evaluated the metabolic patterns of TETs. Metabolic scores were constructed to quantify the metabolic patterns of individual tumors. Subsequent investigation of distinct clinical outcomes and the immune landscape associated with the metabolic scores was conducted. Two distinct metabolic patterns and differential metabolic scores were identified between TETs, which were enriched in a variety of biological pathways and correlated with clinical outcomes. In particular, a high metabolic score was highly associated with poorer survival outcomes and immunosuppressive status. More importantly, the expression of two prognostic genes (ASNS and BLVRA) identified from differential metabolism-related genes was significantly associated with patient survival and may play a key role in the tumorigenesis of TETs. Our findings suggest that differential metabolic patterns in TETs are relevant to tumorigenesis and clinical outcome. Specific transcriptomic alterations in differential metabolism-related genes may serve as predictive biomarkers of survival outcomes and potential targets for the treatment of patients with TETs.
Midazolam as a Probe for Heterotropic Drug-Drug Interactions Mediated by CYP3A4

Human cytochrome P450 CYP3A4 is involved in the processing of more than 35% of current pharmaceuticals and therefore is responsible for multiple drug-drug interactions (DDI). In order to develop a method for the detection and prediction of the possible involvement of new drug candidates in CYP3A4-mediated DDI, we evaluated the application of midazolam (MDZ) as a probe substrate. MDZ is hydroxylated by CYP3A4 in two positions: 1-hydroxy MDZ formed at lower substrate concentrations, and up to 35% of 4-hydroxy MDZ at high concentrations. The ratio of the formation rates of these two products (the site of metabolism ratio, SOM) was used as a measure of allosteric heterotropic interactions caused by effector molecules using CYP3A4 incorporated in lipid nanodiscs. The extent of the changes in the SOM in the presence of effectors is determined by chemical structure and is concentration-dependent. MD simulations of CYP3A4 in the lipid bilayer suggest that experimental results can be explained by the movement of the F-F’ loop and concomitant changes in the shape and volume of the substrate-binding pocket. As a result of PGS binding at the allosteric site, several residues directly contacting MDZ move away from the substrate molecule, enabling the repositioning of the latter for minor product formation.
Multi-fidelity Nonlinear Aeroelastic Analysis of a Strut-braced Ultra-high Aspect Ratio Wing Configuration

Nonlinear aeroelasticity of a strut-braced ultra-high aspect ratio wing aircraft is investigated using a multi-fidelity simulation environment. A baseline aeroelastic solver based on an unsteady vortex-lattice method and geometrically-exact composite beam model is coupled with a data-driven model order reduction tool based on high-fidelity aerodynamics. This provides sectional corrections, retrieved from a basis created using proper orthogonal decomposition, to the lower-order tools. Those corrections incorporate the three-dimensional and compressibility effects of the full strut-brace wing aircraft geometry and thus result in a computationally-efficient analysis framework suitable for multi-disciplinary design optimization. Verification of the reconstruction process is first presented, and the static and dynamic aeroelasticity of the strut-braced wing configuration are finally investigated.
Targeted metabolomics suggests a probable role of the FTO gene in the kynurenine pathway in prediabetes

Background Genome-wide association studies have identified the alpha-ketoglutarate dependent dioxygenase gene (FTO) as the first susceptibility gene of obesity. In the present study, we utilized targeted metabolomics in an attempt to further elucidate mechanisms underlying the action of the FTO gene. Methods This study was part of a health survey of employees of the Electricity Generating Authority of Thailand (n = 79, 10 female and 69 male). Targeted metabolomics was performed by liquid chromatography–mass spectrometry using Biocrates AbsoluteIDQ-p180 kit. Genotyping of FTO rs9939609 was performed by real-time PCR (TaqMan™ MGB probes). Results Using OPLS-DA variable importance in projection (VIP), tryptophan was found to be among the metabolites with the 10 highest VIP scores. Pearson’s correlation analysis showed that kynurenine and tryptophan were positively correlated only in subjects with the rs9939609 A allele (n = 32, r = 0.56, p < 0.001) and the correlation coefficients were significantly higher in subjects having the A allele than in those without the A allele (p < 0.05). Moreover, the kynurenine/tryptophan ratio was significantly associated with the presence of the A allele, independently of body mass index and sex. Conclusions The FTO gene is likely to influences the conversion of tryptophan to kynurenine.
Variability in Susceptibility to Type I Interferon Response and Subgenomic RNA Accumulation Between Clinical Isolates of Dengue and Zika Virus From Oaxaca Mexico Correlate With Replication Efficiency in Human Cells and Disease Severity

Dengue and Zika viruses cocirculate annually in endemic areas of Mexico, causing outbreaks of different magnitude and severity every year, suggesting a continuous selection of Flavivirus variants with variable phenotypes of transmissibility and virulence. To evaluate if Flavivirus variants with different phenotypes cocirculate during outbreaks, we isolated dengue and Zika viruses from blood samples of febrile patients from Oaxaca City during the 2016 and 2019 epidemic years. We compared their replication kinetics in human cells, susceptibility to type I interferon antiviral response, and the accumulation of subgenomic RNA on infected cells. We observed correlations between type I interferon susceptibility and subgenomic RNA accumulation, with high hematocrit percentage and thrombocytopenia. Our results suggest that Flaviviruses that cocirculate in Oaxaca, Mexico, have variable sensitivity to the antiviral activity of type I interferons, and this phenotypic trait correlates with the severity of the disease.
Application of Dual Silane Coupling Agent-Assisted Surface-Modified Quartz Powder in Epoxy Matrix for Performance Enhancement

Quartz powder (QP) is an inorganic filler that is expected to significantly enhance the dielectric and mechanical properties of epoxy (EP)-based composites applied in copper clad laminates and epoxy molding compounds for 5G applications. As is well-known, the performance of the QP–EP composites is directly correlated with the dispersion effect and the compatibility of QP with an EP matrix. Herein, we propose the surface modification method of QP by mixing SCAs of different alkyl chain lengths that contain amino and carbonyl groups. Different characterization methods (FTIR, TGA, XPS, SEM, contact angle measurement, viscosity, and mechanical properties) and molecular dynamics simulation were adopted to study its effect and mechanism. Through dual SCA modification, the viscosity of QP–EP composites was reduced by 11.70%, and the flexural and tensile strengths increased by 16.89% and 30.01%, respectively. In addition, it was revealed that the superiority of dual SCAs originated from the synergistic effect between APTES and SPIS, it was the electrostatic repulsion force between the amino groups of the two SCAs that caused a steric hindrance that activated the steric stabilization effect of SPIS, thus resulting in better dispersion and excellent compatibility. Meanwhile, the amino and carbonyl groups of the SCA interacted with the EP matrix via chemical bonds and hydrogen bonds, thus strengthening the interfacial adhesion between the QP and EP matrix and improving the mechanical performance of QP–EP composites. These results are evidence of the potential of the proposed approach, which is based on the synergistic compounding of SCA with different molecular structures, in powder industrial applications.