Unconventional Signals Research Articles

Users' Perspectives on Multimodal Menstrual Tracking Using Consumer Health Devices

Previous menstrual health literature highlights a variety of signals not included in existing menstrual trackers because they are either difficult to gather or are not typically associated with menstrual health. Since it has become increasingly convenient to collect biomarkers through wearables and other consumer-grade devices, our work examines how people incorporate unconventional signals (e.g., blood glucose levels, heart rate) into their understanding of menstrual health. In this paper, we describe a three-month-long study on fifty participants' experiences as they tracked their health using physiological sensors and daily diaries. We analyzed their experiences with both conventional and unconventional menstrual health signals through surveys and interviews conducted throughout the study. We delve into the various aspects of menstrual health that participants sought to affirm using unconventional signals, explore how these signals influenced their daily behaviors, and examine how multimodal menstrual tracking expanded their scope of menstrual health. Finally, we provide design recommendations for future multimodal menstrual trackers.

Study on the Impact of Pole Spacing on Magnetic Flux Leakage Detection under Oversaturated Magnetization.

Magnetic flux leakage (MFL) inspection employs leakage magnetic fields to effectively detect and locate pipeline defects. The spacing between magnetic poles significantly affects the leakage magnetic field strength. While most detectors typically opt for moderate pole spacing for routine detection, this study investigates the propagation characteristics of MFL signals at small pole spacings (under specimen oversaturated magnetization) and their impact on MFL detection. Through finite element simulation and experiments, it reveals a new signal phenomenon in the radial MFL signal By at small pole spacings, the double peak-valley (DPV) phenomenon, characterized by outer and inner peaks and valleys. Theoretical analysis based on the simulation results elucidates the mechanisms for this DPV phenomenon. Based on this, the impact of defect size, pipe wall thickness, and magnetic pole and rigid brush height on MFL signals under small magnetic pole spacings is examined. It is demonstrated that, under a smaller magnetic pole spacing, a potent background magnetic field manifests in the air above the defect. This DPV phenomenon is generated by the magnetic diffusion and compression interactions between the background and defect leakage magnetic fields. Notably, the intensity of the background magnetic field can be mitigated by reducing the height of the rigid brush. In contrast, the pipe wall thickness and magnetic pole height exhibit a negligible influence on the DPV phenomenon. The emergence of the DPV precipitates a reduction in the peak-to-valley difference within the MFL signal, constricting the depth range of detectable defects. However, the presence of DPV increases the identification of defects with smaller opening sizes. These findings reveal the characterization of the MFL signal under small pole spacing, offering a preliminary study on identifying specific defects using unconventional signals. This study provides valuable guidance for MFL detection.

Targeting of plasmodesmal proteins requires unconventional signals.

Effective cellular signaling relies on precise spatial localization and dynamic interactions among proteins in specific subcellular compartments or niches, such as cell-to-cell contact sites and junctions. In plants, endogenous and pathogenic proteins gained the ability to target plasmodesmata, membrane-lined cytoplasmic connections, through evolution to regulate or exploit cellular signaling across cell wall boundaries. For example, the receptor-like membrane protein PLASMODESMATA-LOCATED PROTEIN 5 (PDLP5), a potent regulator of plasmodesmal permeability, generates feed-forward or feed-back signals important for plant immunity and root development. However, the molecular features that determine the plasmodesmal association of PDLP5 or other proteins remain largely unknown, and no protein motifs have been identified as plasmodesmal targeting signals. Here, we developed an approach combining custom-built machine-learning algorithms and targeted mutagenesis to examine PDLP5 in Arabidopsis thaliana and Nicotiana benthamiana. We report that PDLP5 and its closely related proteins carry unconventional targeting signals consisting of short stretches of amino acids. PDLP5 contains two divergent, tandemly arranged signals, either of which is sufficient for localization and biological function in regulating viral movement through plasmodesmata. Notably, plasmodesmal targeting signals exhibit little sequence conservation but are located similarly proximal to the membrane. These features appear to be a common theme in plasmodesmal targeting.

Muscle-to-Brain Signaling Via Myokines and Myometabolites.

Skeletal muscle health and function are important determinants of systemic metabolic homeostasis and organism-wide responses, including disease outcome. While it is well known that exercise protects the central nervous system (CNS) from aging and disease, only recently this has been found to depend on the endocrine capacity of skeletal muscle. Here, we review muscle-secreted growth factors and cytokines (myokines), metabolites (myometabolites), and other unconventional signals (e.g. bioactive lipid species, enzymes, and exosomes) that mediate muscle-brain and muscle-retina communication and neuroprotection in response to exercise and associated processes, such as the muscle unfolded protein response and metabolic stress. In addition to impacting proteostasis, neurogenesis, and cognitive functions, muscle-brain signaling influences complex brain-dependent behaviors, such as depression, sleeping patterns, and biosynthesis of neurotransmitters. Moreover, myokine signaling adapts feeding behavior to meet the energy demands of skeletal muscle. Contrary to protective myokines induced by exercise and associated signaling pathways, inactivity and muscle wasting may derange myokine expression and secretion and in turn compromise CNS function. We propose that tailoring muscle-to-CNS signaling by modulating myokines and myometabolites may combat age-related neurodegeneration and brain diseases that are influenced by systemic signals.

Mining user interaction patterns in the darkweb to predict enterprise cyber incidents

With the rise in security breaches over the past few years, there has been an increasing need to mine insights from social media platforms to raise alerts of possible attacks in an attempt to defend conflict during competition. In this study, we attempt to build a framework that utilizes unconventional signals from the darkweb forums by leveraging the reply network structure of user interactions with the goal of predicting enterprise-related external cyber attacks. We use both unsupervised and supervised learning models that address the challenges that come with the lack of enterprise attack metadata for ground-truth validation as well as insufficient data for training the models. We validate our models on a binary classification problem that attempts to predict cyber attacks on a daily basis for an organization. Using several controlled studies on features leveraging the network structure, we measure the extent to which the indicators from the darkweb forums can be successfully used to predict attacks. We use information from 53 forums in the darkweb over a span of 17 months for the task. Our framework to predict real-world organization cyber attacks of three different security events suggests that focusing on the reply path structure between groups of users based on random walk transitions and community structures has an advantage in terms of better performance solely relying on forum or user posting statistics prior to attacks.

Forecasting cyberattacks with incomplete, imbalanced, and insignificant data

Having the ability to forecast cyberattacks before they happen will unquestionably change the landscape of cyber warfare and cyber crime. This work predicts specific types of attacks on a potential victim network before the actual malicious actions take place. The challenge to forecasting cyberattacks is to extract relevant and reliable signals to treat sporadic and seemingly random acts of adversaries. This paper builds on multi-faceted machine learning solutions and develops an integrated system to transform large volumes of public data to aggregate signals with imputation that are relevant and predictive of cyber incidents. A comprehensive analysis of the individual parts and the integrated whole demonstrates the effectiveness and trade-offs of the proposed approach. Using 16-months of reported cyber incidents by an anonymized victim organization, the integrated approach achieves up to 87%, 90%, and 96% AUC for forecasting endpoint-malware, malicious-destination, and malicious-email attacks, respectively. When assessed month-by-month, the proposed approach shows robustness to perform consistently well, achieving F-Measure between 0.6 and 1.0. The framework also enables an examination of which unconventional signals are meaningful for cyberattack forecasting.

Modeling the transcriptome of genital tract epithelial cells and macrophages in healthy mucosa versus mucosa inflamed by Chlamydia muridarum infection.

Chlamydia trachomatis urogenital serovars are intracellular bacteria that parasitize human reproductive tract epithelium. As the principal cell type supporting bacterial replication, epithelial cells are central to Chlamydia immunobiology initially as sentries and innate defenders, and subsequently as collaborators in adaptive immunity-mediated bacterial clearance. In asymptomatic individuals who do not seek medical care a decisive struggle between C. trachomatis and host defenses occurs at the epithelial interface. For this study, we modeled the immunobiology of epithelial cells and macrophages lining healthy genital mucosa and inflamed/infected mucosa during the transition from innate to adaptive immunity. Upper reproductive tract epithelial cell line responses were compared to bone marrow-derived macrophages utilizing gene expression microarray technology. Those comparisons showed minor differences in the intrinsic innate defenses of macrophages and epithelial cells. Major lineage-specific differences in immunobiology relate to epithelial collaboration with adaptive immunity including an epithelial requirement for inflammatory cytokines to express MHC class II molecules, and a paucity and imbalance between costimulatory and coinhibitory ligands on epithelial cells that potentially limits sterilizing immunity (replication termination) to Chlamydia-specific T cells activated with limited or unconventional second signals.

Searching for unconventional seismic signals on a subduction zone with a submerged forearc: OBS offshore the Lesser Antilles

Abstract Detecting unconventional seismic signals related to subduction zone processes at depth in continuous ocean bottom seismometer (OBS) records requires the analysis and identification of noise due to instrumental problems, deployment sites or sea state conditions. The temporary OBS deployment at the Lesser Antilles subduction zone provides new insights into the feasibility of detecting unconventional signals such as non volcanic tremor (NVT), long-period (LP) or ultra-long period (ULP) events. Analysis of noise at an array comprising several sites and types of instruments and comparison with recordings on land shows transients in the noise. Episodes can be identified considering the diversity of sites and instrument types and comparing the seismic signals with meteorological and oceanographic data. In order to reliably detect NVT (1–10 Hz) originating from inside the solid Earth, one must first characterize noise induced by the activity of the atmosphere and hydrosphere at the sea-bottom as well as on land. The semidiurnal modulation of noise amplitude can be shown here not to be due to that of the NVT from a seismic source at depth which is related to the subduction interplate and whose activity is modulated by the tidal stresses as inferred for other megathrusts on emerged forearcs. Here, the semidiurnal modulation is rather due to the effect of the tides themselves, such as tidal currents, since they do not affect all types and all components of the unique multi-station array of OBS that could be deployed on this submerged forearc. The short period cut-off of the strong noise due to ocean surface infragravity waves increases to longer periods with OBS depth, thereby increasing the observational window with low noise to lower frequencies, and deep OBS sites may be advantageous for detecting LP events.

Thermal-Noise-Exploiting Operations of Single-Electron Majority Logic Circuits with Conventional Clock Signals

This paper describes a thermal-noise-exploiting single-electron majority logic circuit. The circuit is based on a single-electron majority logic circuit using an irreversible single- electron box that was proposed in 2003. To correctly operate the original circuit, unconventional two-step clock signals are needed to decide and hold logical outputs. Moreover, the temperature is set to 0 K because the circuit is very sensitive to thermal noise. This circuit uses conventional clock signals that lack the first step of the two-step clocks used for deciding the output, and the circuit is placed in a thermal-noise environment. The key for correct circuit operation is to base the circuit system on a model of noise- exploiting neural networks, i.e., the stochastic resonance system. The system can stochastically detect a weak input signal with the help of external noise. Thermal energy in the proposed circuit should compensate for lack of the first step of the two-step clocks. In this study, the thermal-noise-exploiting majority logic circuit was designed, and its operation was tested by using a Monte Carlo simulation. As a result, the circuit operation was evaluated, and the circuit performance was found to be improved by increasing the temperature to T ≤ 5 K, i.e., the proposed circuit can exploit thermal noise energy for correct operation.

Summary of Non-traditional Methods for Metal Detection and Discrimination

Abstract This paper describes three different possibilities how to detect and distinguish between different metal garbage and mine (especially Anti-Personnel mines - AP) or UXO (unexploded ordnance). A comparison of three unconventional excitation polyharmonic signals for an eddy current metal detector is presented. These signals are linear frequency sweep sinusoidal, step sweep sinusoidal, and sinc signals. Thanks to this we obtained a frequency characteristic of a detected object over a wide range of frequencies and obtained more detailed view about object than with classical methods. Amplitude and phase spectra, polar graphs as well as real and imaginary parts ot detector signal output are presented. Based on the measurements and the analyses, the distinguishing between different objects can be done in terms of the electromagnetic properties (conductivity and permeability). Polar graphs could be used for an object's interpretation and for the manual discrimination.

Phenomenological Aspects of the Next-to-Minimal Supersymmetric Standard Model

The motivations for the NMSSM are reviewed, and possible unconventional signals for Higgs and sparticle production at the LHC are discussed. In the presence of a light pseudoscalar, the SM-like Higgs scalar can decay dominantly into a 4-tau final state. In the fully constrained NMSSM with mSUGRA-like soft SUSY breaking terms, the correct dark matter relic density is obtained for a singlino-like LSP which modifies considerably all sparticle decay chains.

Children with Autism Spectrum Disorders: Three Case Studies

Children with Autism Spectrum Disorders: Three Case Studies

A common language: Using B. F. Skinner's Verbal Behavior for assessment and treatment of communication disabilities in SLP-ABA.

Introduction During the last decade there has been a growing trend for direct collaboration between the fields of speech-language pathology (SLP) and applied analysis (ABA). A common overlap between the focus of the two fields is in the area of communication assessment and intervention for the purposes of enhanced interaction skills and management of inappropriate behaviors resulting from inadequate communication skills (Koenig and Gerenser, 2006). Disagreements among professionals from both fields often can be a result of a difference in terminology. Take for example, the definition of the term A definition adopted by the American Speech-Language Hearing Association was developed by the National Joint Committee for the Communicative needs of Persons with Severe Disabilities (1991, p. 2). Any act by which one person gives to or receives from another person information about that person's needs, desires, perceptions, knowledge or affective states. Communication may be intentional or unintentional, may involve conventional or unconventional signals, may take linguistic or nonlinguistic forms, and may occur through spoken or other modes. This definition emphasizes the shared meaning established between a speaker and a listener. The Joint Committee concluded, Thus, all persons do communicate in some way. Additionally, the success of a communicative exchange could depend on the listener happening to witness the speaker's and interpreting that as communicative. The 1957 publication of B.F. Skinner's Verbal Behavior provided the field of ABA with a definition of communication. Skinner refers to behavior as reinforced through the mediation of other people (p.2) and specified that the 'listener' must be responding in ways which have been conditioned precisely in order to reinforce the of the speaker [by the verbal community] ... In other words, a speaker acts in a manner that is under the stimulus control of an audience (a listener) and the listener then provides the reinforcing consequence. It is through reinforcement of a specific verbal community (the French, the English, the Spanish) that a child learns the grammar and vocabulary of a particular community. The definitions from both fields emphasize that communication can occur in many modalities, just the spoken modality. A source of confusion in the field of SLP has been in defining the terms speech, communication, and verbal. Reports of a student including phrases such as not verbal, or non-verbal, can lead to erroneous conclusions. A speech pathologist might assume that this means that the student is yet speaking. A person using Skinner's definition would conclude that the student has no communication skills at all in any modality. The less ambiguous terminology to describe the student who is speaking would be non-speaking or non-vocal. This could mean that the student has a sophisticated language system in a non-speech modality such as pictures, sign language, or writing. Skinner's definition also helps us to identify behaviors of a student that are verbal behavior. Behaviors that lead to direct access to reinforcing consequences are communicative because access to those consequences is dependent upon another person. For example if a student goes to a table and picks up a we would say that this is communicative as the action was aimed directly at the book. On the other hand, if the student says to the teacher sitting at the table, I want that book, and the teacher hands it to the student, we would say that this is verbal behavior. The purpose of this paper is to provide an overview of Skinner's analysis of verbal and its application to assessment and remediation of communication deficits. A description of Skinner's primary verbal operants will be provided. …

An unconventional dileucine-based motif and a novel cytosolic motif are required for the lysosomal and melanosomal targeting of OA1

The protein product of the gene responsible for ocular albinism type 1, named OA1, is a pigment-cell-specific membrane glycoprotein, displaying features of G-protein-coupled receptors, yet exclusively localized to late endosomes, lysosomes and melanosomes. To dissect the signals responsible for the intracellular localization of OA1, we generated chimeric proteins consisting of the cytosolic domains of OA1 fused to the lumenal and transmembrane domains of LAMP1; in addition, we generated missense and deletion mutants of full-length OA1. Using this approach, we identified two separate sorting signals that are both necessary and sufficient for intracellular retention, as well as lysosomal and melanosomal localization, in melanocytic and non-melanocytic cells. These sorting signals are an unconventional dileucine motif within the third cytosolic loop and a novel motif, characterized by a tryptophan-glutamic acid doublet, within the C-terminal tail. Both motifs must be mutated to promote the plasma membrane localization of OA1, suggesting that they can independently drive its intracellular targeting. In addition, both motifs act similarly as lysosomal sorting signals in non-melanocytic cells, but appear to carry different specificities in melanocytic cells. Our findings indicate that OA1 contains multiple unconventional signals responsible for its lysosomal and melanosomal localization, and reveal a remarkable and unforeseen complexity in the regulation of polytopic protein sorting to specialized secretory organelles.