Limited Number Of States Research Articles

Virtual Clinic Telehealth Abortion Services in the United States One Year After Dobbs: Landscape Review.

Telehealth abortion has taken on a vital role in maintaining abortion access since the Dobbs v. Jackson Women's Health Organization Supreme Court decision. However, little remains known about the landscape of new telehealth-only virtual clinic abortion providers that have expanded since telehealth abortion first became widely available in the United States in 2021. This study aimed to (1) document the landscape of telehealth-only virtual clinic abortion care in the United States, (2) describe changes in the presence of virtual clinic abortion services between September 2022, following the Dobbs decision, and June 2023, and (3) identify structural factors that may perpetuate inequities in access to virtual clinic abortion care. We conducted a repeated cross-sectional study by reviewing web search results and abortion directories to identify virtual abortion clinics in September 2022 and June 2023 and described changes in the presence of virtual clinics between these 2 periods. In June 2023, we also described each virtual clinic's policies, including states served, costs, patient age limits, insurance acceptance, financial assistance available, and gestational limits. We documented 11 virtual clinics providing telehealth abortion care in 26 states and Washington DC in September 2022. By June 2023, 20 virtual clinics were providing services in 27 states and Washington DC. Most (n=16) offered care to minors, 8 provided care until 10 weeks of pregnancy, and median costs were US $259. In addition, 2 accepted private insurance and 1 accepted Medicaid, within a limited number of states. Most (n=16) had some form of financial assistance available. Virtual clinic abortion providers have proliferated since the Dobbs decision. We documented inequities in the availability of telehealth abortion care from virtual clinics, including age restrictions that exclude minors, gestational limits for care, and limited insurance and Medicaid acceptance. Notably, virtual clinic abortion care was not permitted in 11 states where in-person abortion is available.

Development of a model of the information and analytical system for making decisions on detecting failures of information transmission channels

The object of the research is the channels of information transmission during the control of the information-analytical decision-making system. The development of high technologies and computing capabilities ensures the evolutionary development of smart technologies and socio-cyber-physical systems on the one hand. On the other hand, it forms the integration of targeted (mixed) attacks with the possibility of integration with social engineering methods. In addition, mobile technologies significantly increase the possibilities of data transmission speed. However, this only provides the authentication service, which does not provide a full range of security services. Under such conditions, an urgent task at the decision-making stage is the use of auxiliary systems that ensure the adequacy of decisions and the promptness of their adoption. The proposed mathematical model of the information and analytical system allows to calculate the main technical characteristics of information transmission channels and identify their possible failures. The use of an information and analytical system simplifies the decision-making process, allows to increase the reliability of such decisions due to an increase in the level of automation. Increasing the level of automation in the decision-making process removes subjective factors and the decision depends on the availability of information. Therefore, the reliability of the information transmission channels of the information and analytical system significantly affects the quality of the decisions made. The developed model allows to ensure the required level of reliability of information transmission channels. The obtained results are explained by determining the dependence between the parameters of the information and analytical system and their influence on the quality of information transmission through channels. The results of the study can be used in practice when considering systems with a limited number of states during operation

Multi-sensors search for lost moving targets using unrestricted effort

This paper addresses the problem of searching for multiple targets using multiple sensors, where targets move randomly between a limited number of states at each time interval. Due to the potential value or danger of the targets, multiple sensors are employed to detect them as quickly as possible within a fixed number of search intervals. Each search interval has an available search effort and an exponential detection function is assumed. The goal is to develop an optimal search strategy that distributes the search effort across cells in each time interval and calculates the probability of not detecting the targets throughout the entire search period. The optimal search strategy that minimizes this probability is determined, the stability of the search is analyzed, and some special cases are considered. Additionally, we introduce the $M$-cells algorithm.

Adaptive variational low-rank dynamics for open quantum systems

We introduce a model-independent method for the efficient simulation of low-entropy systems, whose dynamics can be accurately described with a limited number of states. Our method leverages the time-dependent variational principle to efficiently integrate the Lindblad master equation, dynamically identifying and modifying the low-rank basis over which we decompose the system's evolution. By dynamically adapting the dimension of this basis, and thus the rank of the density matrix, our method maintains optimal representation of the system state, offering a substantial computational advantage over existing adaptive low-rank schemes in terms of both computational time and memory requirements. We demonstrate the efficacy of our method through extensive benchmarks on a variety of model systems, with a particular emphasis on multiqubit bosonic codes, a promising candidate for fault-tolerant quantum hardware. Our results highlight the method's versatility and efficiency, making it applicable to a wide range of systems characterized by arbitrary degrees of entanglement and moderate entropy throughout their dynamics. We provide an implementation of the method as a Julia package, making it readily available to use. Published by the American Physical Society 2024

Condensation of preformed charge density waves in kagome metals

Charge density wave (CDW) is a spontaneous spatial modulation of charges in solids whose general microscopic descriptions are yet to be completed. Kagome metals of AV3Sb5 (A = K, Rb, Cs) provide a chance to realize CDW intertwined with dimensional effects as well as their special lattice. Here, based on a state-of-the-art molecular dynamics simulation, we propose that their phase transition to CDW is a condensation process of incoherently preformed charge orders. Owing to unavoidable degeneracy in stacking charge orders, phases of preformed orders on each layer are shown to fluctuate between a limited number of states with quite slower frequencies than typical phonon vibrations until reaching their freezing temperature. As the size of interfacial alkali atom increases, the fluctuations are shown to counterbalance the condensation of orderings, resulting in a maximized transition temperature for RbV3Sb5. Our results resolve controversial observations on their CDWs, highlighting a crucial role of their interlayer interactions.

Amplitude-optimized Koopman-linear flow estimator for wind turbine wake dynamics: Approximation, prediction and reconstruction

The low-order modeling of wind turbine dynamic wake is a challenging problem, which requires approximating high-dimensional, nonlinear dynamic systems with a limited number of states and linear structures. The Koopman-linear flow estimator is regarded as a promoting method in this area to approximate the dynamic wake field from a few physical-measured states. This paper presents optimization methods for the Koopman-linear flow estimator to improve its generalization applicability and modeling accuracy in specific applications. Firstly, the flow estimator’s wake field prediction process is organized using Koopman modes and amplitudes; both are identified initially. Then, a optimization method is proposed to optimize the Koopman amplitudes for a given application scenario, which maintains a consistent form for uncontrolled and controlled systems based on the error-source analysis. After this, a sequential particle swarm optimization algorithm is adopted, which improves the computationally-intensive problem during sensor configuration optimization. The proposed algorithm quickly solves a feasible and optimized sensor configuration plan instead of the unavailable global-optimal one. The verification results show two conclusions: On the one hand, the nonlinearity during the yaw-induced wake deflection process is evident, which poses a significant challenge to the linear low-order approximation of the dynamic wake field. On the other hand, the proposed optimization methods highly improve the dynamic wake modeling accuracy under free-wake and yaw-controlled scenarios. Sparse sampling is necessary for dynamic wake behavior study in industrial. This paper solves the incomplete measurements and wake deflection nonlinearity problem caused by sparse sampling and promotes the generalization applicability for specific applications.

MSSA: Constant Time State Search through Multi-Scope State Area

In the stateful data plane, the switch can record the state and forward packets based on the local state. This approach makes it possible to integrate complex network applications into the data plane, thus reducing the amount of communication required between the switch and the controller. However, due to the time it takes to look up the state for packets, packet-forwarding latency has increased. With increased network traffic, a large number of states may be recorded in the switch, and the problem of increased packet-forwarding latency caused by the lookup state becomes more serious. In this paper, we propose the multi-scope state area (MSSA) for recording state inside the switch, which can achieve a fixed-time state lookup in a large-scale state. MSSA divides the state sharing scope by associating with the switch’s multiple match–action tables, and the shared scope is used to determine the state area for recording state. When processing a packet, the state required will only be in a limited number of states that are recorded in a few state areas. We implemented a prototype pipeline that supports MSSA based on Intel’s DPDK framework and investigated the effect of state type, number, location, and comparison method on state search/insertion time. The results show that the cost of MSSA search state is constant, regardless of the number of states, and MSSA has a high space utilization rate.

Adapting to the Behavior of Environments with Bounded Memory

We study the problem of synthesizing implementations from temporal logic specifications that need to work correctly in all environments that can be represented as transducers with a limited number of states. This problem was originally defined and studied by Kupferman, Lustig, Vardi, and Yannakakis. They provide NP and 2-EXPTIME lower and upper bounds (respectively) for the complexity of this problem, in the size of the transducer. We tighten the gap by providing a PSPACE lower bound, thereby showing that algorithms for solving this problem are unlikely to scale to large environment sizes. This result is somewhat unfortunate as solving this problem enables tackling some high-level control problems in which an agent has to infer the environment behavior from observations. To address this observation, we study a modified synthesis problem in which the synthesized controller must gather information about the environment's behavior safely. We show that the problem of determining whether the behavior of such an environment can be safely learned is only co-NP-complete. Furthermore, in such scenarios, the behavior of the environment can be learned using a Turing machine that requires at most polynomial space in the size of the environment's transducer.

Renormalized spectrum of quasiparticle in limited number of states, strongly interacting with two-mode polarization phonons at T=0 K

Within unitary transformed Hamiltonian of Fröhlich type, using the Green's functions method, exact renormalized energy spectrum of quasiparticle strongly interacting with two-mode polarization phonons is obtained at T=0 K in a model of the system with limited number of its initial states. Exact analytical expressions for the average number of phonons in ground state and in all satellite states of the system are presented. Their dependences on a magnitude of interaction between quasiparticle and both phonon modes are analyzed.

Prognostics for Deteriorating Systems Under Indirect Discrete Monitoring and Random Failure

Generally, the internal states of most engineering systems are inaccessible to sensors under operational conditions, permitting indirect measurements and failures to be observed discretely. For this type of system, a class of proportional hazard (PH) models with multistate process have been proposed for performing prognostics. However, existing studies use a constant degradation mechanism with a very limited number of states, which may fail to model the actual deterioration of the system. Therefore, this article presents a novel PH model that utilizes a nonconstant degradation mechanism with a large number of states to perform health prognostics. A matrix partition-based approximation method is developed to include all the possible state transitions and to estimate important health quantities of the system, such as conditional reliability (CR), mean remaining useful life (MRUL), and remaining useful life distribution (RULD). An online prognostic scheme based on this matrix approach is presented to provide an update with the latest health quantities of the system. The proposed approach provides appealing computational features and avoids difficulties in calculating uncountable transitions for PH model-based prognostics. The effectiveness of the proposed method is demonstrated via a case of helical gearboxes under indirect monitoring and random failure conditions.

Laboratory Blood-Based Testing for Non-Lyme Disease Tick-Borne Infections at a National Reference Laboratory.

We evaluated trends in non-Lyme disease tick-borne disease (NLTBI) testing at a national reference laboratory. Testing data performed at Quest Diagnostics during 2010 to 2016 were analyzed nationally and at the state level. Testing and positivity for most NLTBIs increased dramatically from 2010 through 2016 based on testing from a large reference laboratory. The number of positive cases, though not as stringent as criteria for public health reporting, generally exceeds that reported by the Centers for Disease Control and Prevention. The frequency of NLTBI in the US is seasonal but testing activity and positive test results are observed throughout all months of the year. Positive results for NLTBI testing mostly originated from a limited number of states, indicating the geographic concentration and distribution of NLTBIs reported in this study. This report provides an important complementary source of data to best understand trends in and spread of NLTBI.

National Systematic Legal Review of State Policies on Emergency Medical Services Licensure Levels' Authority to Administer Opioid Antagonists

Objective: Previous research conducted in November 2013 found there were a limited number of states and territories in the United States (US) that authorize emergency medical technicians (EMTs) and emergency medical responders (EMRs) to administer opioid antagonists. Given the continued increase in the number of opioid-related overdoses and deaths, many states have changed their policies to authorize EMTs and EMRs to administer opioid antagonists. The goal of this study is to provide an updated description of policy on EMS licensure levels' authority to administer opioid antagonists for all 50 US states, the District of Columbia (DC), and the Commonwealth of Puerto Rico (PR). Methods: State law and scopes of practice were systematically reviewed using a multi-tiered approach to determine each state's legally-defined EMS licensure levels and their authority to administer an opioid antagonist. State law, state EMS websites, and state EMS scope of practice documents were identified and searched using Google Advanced Search with Boolean Search Strings. Initial results of the review were sent to each state office of EMS for review and comment. Results: As of September 1, 2017, 49 states and DC authorize EMTs to administer an opioid antagonist. Among the 40 US jurisdictions (39 states and DC) that define the EMR or a comparable first responder licensure level in state law, 37 states and DC authorize their EMRs to administer an opioid antagonist. Paramedics are authorized to administer opioid antagonists in all 50 states, DC, and PR. All 49 of the US jurisdictions (48 states and DC) that define the advanced emergency medical technician (AEMT) or a comparable intermediate EMS licensure level in state law authorize their AEMTs to administer an opioid antagonist. Conclusions: 49 out of 52 US jurisdictions (50 states, DC, and PR) authorize all existing levels of EMS licensure levels to administer an opioid antagonist. Expanding access to this medication can save lives, especially in communities that have limited advanced life support coverage.

Current Epidemiology of Serogroup W Meningococcal Disease—United States, 2010–2015

BackgroundSerogroup W (NmW) meningococcal disease is a rare but severe infection. Following an NmW outbreak after the Hajj in 2000, NmW disease, predominantly caused by sequence type (ST)-11 clonal complex (cc), rapidly increased in South Africa, South America, and the UK. We describe NmW meningococcal disease epidemiology in the USA during 2010–2015.MethodsData were collected from the National Notifiable Diseases Surveillance System, Active Bacterial Core surveillance, and state health departments. Isolates were serogrouped via slide agglutination and real-time polymerase chain reaction. For cases lacking a serogroup result at CDC, the state result was used. Case-fatality ratios (CFR) were calculated using the proportion of cases with known outcomes as the denominator. cc and ST were determined using multilocus sequence typing (MLST).ResultsFrom 2010 to 2015, 3,504 meningococcal disease cases were reported to CDC; 2,976 (85%) had a serogroup result, of which 290 (10%) were NmW. Although the number of NmW cases reported annually remained fairly stable (range: 40–57), the total number of reported meningococcal disease cases decreased by 60%, and the proportion of cases due to NmW increased from 6% (42/830) in 2010 to 12% (40/332) in 2015. The majority of NmW cases were reported from five states: Florida (n = 106), California (n = 31), New York (n = 25), Georgia (n = 19), and Oregon (n = 11). Half of people with NmW disease were male, 185 (64%) were white, and 84 (29%) were Hispanic. The median age was 51 years (interquartile range: 26–70). Overall, 20% (52/259) of NmW cases were fatal, compared with CFRs for serogroups B (15%), Y (18%), or C (24%). NmW CFR was highest among adults aged 50–59 years (38%). MLST results were available for 119 (41%) of NmW cases: 76 (64%) were cc11, 40 (34%) were cc22, and 1 each were cc23, cc32, and an unassigned cc. cc appeared to be geographically associated: cc11 was concentrated in Florida and Georgia, while cc22 predominated on the West coast. Within cc11, the majority of isolates (86%) were ST-11, and within cc22 the majority (73%) were ST-22.ConclusionA rapid increase in NmW disease has not been observed in the USA. Most NmW cases were reported in a limited number of states, with geographic differences in clonal complex.Disclosures All authors: No reported disclosures.

Stochastic method of investigating perturbed motion of a space vehicle in the atmosphere

When space vehicles (SVs) are moving in the atmosphere detailed accounting of the influence of external perturbation factors is quite difficult: they are either unknown or have a complex nature. This necessitates development of methods to solve the problems of controlling SVs in conditions of uncertainty. A stochastic method of investigating perturbed paths of space vehicles in the atmosphere has been elaborated. The method is based on the mathematical theory of continuous Markovian processes. The principle of reduction from deterministic description of space vehicle motion to the stochastic one is applied. A SV is supposed to be in a limited number of states that are determined by a previously chosen algorithm of phase space discretization. Differential Kolmogorov equations for determining the probabilities of a SV being in each of the states and relationships for the calculation of mathematical expectations of SV space phases are set up. Relationships for calculating the rates of SV transition from one state to another are developed and validated. Ways of reducing the duration of the processes of calculating SV flight paths are proposed. Analytical relationships for determining the values of phase coordinates are formulated. Numerical results of calculating flight paths in a wide range of boundary conditions of SV design characteristics are given. The possibility of applying the proposed method for the analysis of SV motion in the atmosphere in conditions of conditions of flight indeterminacy is shown.

The optimal thermo-optical properties and energy saving potential of adaptive glazing technologies

The development of dynamic building envelope technologies, which adapt to changing outdoor and indoor environments, is considered a crucial step towards the achievement of the nearly Zero Energy Building target. It is currently not possible to evaluate the energy saving potential of innovative adaptive transparent building envelopes in an accurate manner. This creates difficulties in selecting between competing technologies and is a barrier to systematic development of these innovative technologies. The main aim of this work is to develop a method for devising optimal adaptive glazing properties and to evaluate the energy saving potential resulting from the adoption of such a technology. The method makes use of an inverse performance-oriented approach, to minimize the total primary energy use of a building. It is applied to multiple case studies (office reference room with 4 different cardinal orientations and in three different temperate climates) in order to evaluate and optimise the performance of adaptive glazing as it responds to changing boundary conditions on a monthly and daily basis. A frequency analysis on the set of optimised adaptive properties is subsequently performed to identify salient features of ideal adaptive glazing. The results show that high energy savings are achievable by adapting the transparent part of the building envelope alone, the largest component being the cooling energy demand. As expected, the energy savings are highly sensitive to: the time scale of the adaptive mechanisms; the capability of the facade to adapt to the outdoor climatic condition; the difference between outdoor climatic condition and the comfort range. Moreover important features of the optimal thermo-optical properties are identified. Of these, one of the most important findings is that a unique optimised technology, varying its thermo-optical properties between a limited number of states could be effective in different climates and orientations. 2015 The Authors. Published by Elsevier Ltd. This is an open access article under the CC BY license (http://

Target States and Japan's Public Support for Military Action: A Survey Experimental Approach

Most previous research examining public support for military action is either theoretical and generalized or narrowly focused on a limited number of states. Few studies have examined the determinants of public support for military action in East Asia, although the region has witnessed growing intensities between Japan and its neighboring states in recent years. To explore the circumstances under which the Japanese public will consent to military action when facing territorial disputes with its neighbors, this study conducted a survey experiment in Japan. According to statistical analyses of the results, if the target state is an ally of the U.S. or if Japan’s economy is highly dependent on the target state, the Japanese public tends to oppose military action. In addition, whether the target state was invaded by Japan during WWII has no significant influence. Finally, younger generations of Japanese are more inclined toward peace than older generations.

Balancing adequacy and affordability?: Essential Health Benefits under the Affordable Care Act

The Essential Health Benefits provisions under the Affordable Care Act require that eligible plans provide coverage for certain broadly defined service categories, limit consumer cost-sharing, and meet certain actuarial value requirements. Although the Department of Health and Human Services (HHS) was tasked with the regulatory development of these EHB under the ACA, the department quickly devolved this task to the states. Not surprisingly, states fully exploited the leeway provided by HHS, and state decision processes and outcomes differed widely. However, none of the states took advantage of the opportunity to restructure fundamentally their health insurance markets, and only a very limited number of states actually included sophisticated policy expertise in their decisionmaking processes. As a result, and despite a major expansion of coverage, the status quo ex ante in state insurance markets was largely perpetuated. Decisionmaking for the 2016 revisions should be transparent, included a wide variety of stakeholders and policy experts, and focus on balancing adequacy and affordability. However, the 2016 revisions provide an opportunity to address these previous shortcomings.

Progressive increase in mtDNA 3243A>G heteroplasmy causes abrupt transcriptional reprogramming.

Variation in the intracellular percentage of normal and mutant mitochondrial DNAs (mtDNA) (heteroplasmy) can be associated with phenotypic heterogeneity in mtDNA diseases. Individuals that inherit the common disease-causing mtDNA tRNA(Leu(UUR)) 3243A>G mutation and harbor ∼10-30% 3243G mutant mtDNAs manifest diabetes and occasionally autism; individuals with ∼50-90% mutant mtDNAs manifest encephalomyopathies; and individuals with ∼90-100% mutant mtDNAs face perinatal lethality. To determine the basis of these abrupt phenotypic changes, we generated somatic cell cybrids harboring increasing levels of the 3243G mutant and analyzed the associated cellular phenotypes and nuclear DNA (nDNA) and mtDNA transcriptional profiles by RNA sequencing. Small increases in mutant mtDNAs caused relatively modest defects in oxidative capacity but resulted in sharp transitions in cellular phenotype and gene expression. Cybrids harboring 20-30% 3243G mtDNAs had reduced mtDNA mRNA levels, rounded mitochondria, and small cell size. Cybrids with 50-90% 3243G mtDNAs manifest induction of glycolytic genes, mitochondrial elongation, increased mtDNA mRNA levels, and alterations in expression of signal transduction, epigenomic regulatory, and neurodegenerative disease-associated genes. Finally, cybrids with 100% 3243G experienced reduced mtDNA transcripts, rounded mitochondria, and concomitant changes in nuclear gene expression. Thus, striking phase changes occurred in nDNA and mtDNA gene expression in response to the modest changes of the mtDNA 3243G mutant levels. Hence, a major factor in the phenotypic variation in heteroplasmic mtDNA mutations is the limited number of states that the nucleus can acquire in response to progressive changes in mitochondrial retrograde signaling.

Empirical Yield-Curve Dynamics, Scenario Símulation and Risk-Measures

This paper has two objectives. First we will construct a general model for the variation in the term structure of interest rates, or to put it another way, we will define a general model for the shift function. Secondly, we will specify a Risk model which uses the shift function derived in the first part of the paper as its main building block. Using Principal Component Analysis (PCA) we show that it takes a 4 factor model to explain the variation in the term structure of interest rates over the period from the beginning of 2002 to early-2012. These 4 factors can be called a Slope factor, a Short-Curvature Factor, a Short Factor and a Curvature Factor. Using the methodology of Heath, Jarrow and Morton (1990) we now specify a 4-factor model for the dynamic in the term structure of interest-rates. This 4-factor model is afterwards being extended to have a stochastic volatility part, which we assume is to be modelled with a GARCH(1,1) process. The resulting 4-factor yield-curve model belongs to the class of USV (unspanned stochastic volatility) models, as the volatility part is un-correlated with the PCA model for the variation in the yield-curve. Our Risk-Model relies on the scenario simulation procedure of Jamshidian and Zhu (1997). The general idea behind the scenario simulation procedure is to limit the number of portfolio evaluations by using the factor loadings derived in the first part of paper and then specify particular intervals for the Monte Carlo simulated random numbers and assign appropriate probabilities to these intervals (states). Our overall conclusion is the following: •The Jamshidian and Zhu scenario simulation methodology is best suited for the calculation of the Risk-Measure ETL - less for VaR. •We find that the scenario simulation procedure is computational efficient, because we with a limited number of states is capable of deriving robust approximations of the probability distribution. •We also find that it is very useful for non-linear securities (Danish Mortgage-Backed-Bonds MBBs), and argue that the method is feasible for large portfolios of highly complex non-linear securities - for example Danish MBBs. •Backtesting the Risk-Model setup during 2008 showed some very promising results as we were able to capture the extreme price-movements that were observed in the market.

Cycle indices of an automaton

The notion of cycle indices of an automaton is introduced as a pair of positive parameters (b, q) effectively evaluated by the automaton. It is shown that the totality of periods of constant automata which may be represented as superpositions of a given automaton, Boolean functions, and the delay element, coincides with the variety of divisors of the members of the geometric progression b, bq, bq2,... This suggests an algorithm for checking the expressibility of constant automata, as well as a theorem on the verification of the expressibility of the totality of all automata with a limited number of states.