Switching Probability Research Articles

Patients and nursing-related factors associated with switching from peritoneal dialysis to hemodialysis: A cross-sectional survey.

The study aimed at analyzing patients and nursing-related factors associated with switching from peritoneal dialysis to hemodialysis. A telephone survey with 574 patients receiving care at six peritoneal dialysis centers of the Mexican Institute of Social Security was conducted: 64.3% were on peritoneal dialysis, and 35.7% had transitioned from peritoneal dialysis to hemodialysis. Data were collected on participants' sociodemographic and clinical characteristics, peritoneal dialysis center size, and nursing workload. Descriptive, bivariate, and multiple Poisson regression analyses were performed. Factors associated with an increased probability of switching from peritoneal dialysis to hemodialysis were a history of catheter dysfunction, peritonitis, and being treated in a large peritoneal dialysis center with a low (<50 patients per nurse per month) or high nursing workload (>70 patients per nurse per month) located in the State of Mexico, compared to a medium-size peritoneal dialysis center with a moderate workload (50-70 patients per nurse per month). To decrease the odds of switching from peritoneal dialysis to hemodialysis, improvement programs should aim to limit nurses' workload to 50-70 patients per nurse per month and implement evidence-based nursing interventions to prevent, detect, and manage peritonitis and peritoneal catheter dysfunction.

“Tone at the top”: management’s discussion and analysis and audit quality

PurposeThis paper aims to investigate whether the managers’ emphasis on audit in the management’s discussion and analysis (MD&A) section of the 10-K filing, as part of the firm’s “tone at the top,” is linked to audit quality.Design/methodology/approachAdopting a computational linguistics approach, the authors measure the manager’s audit emphasis as the frequency of audit-related words in the MD&A. The authors then assess the relationship between audit emphasis and audit quality with ordinary least squares and probit regression models.FindingsThis study finds that the manager’s audit emphasis, proxied by the count of audit-related words, is positively associated with audit fees, audit delay, the appointment and retention of Big 4 and industry-specialist auditors, and the probability of switching to Big 4 auditors, while negatively linked to abnormal accruals and the possibility of financial misstatements.Research limitations/implicationsThe audit emphasis measure suffers from limitations. The computer program determining audit emphasis may misinterpret words in the MD&A. Researchers need to consider procedures to minimize misinterpretations.Practical implicationsFrequency of audit words in the MD&A reflects the firm’s aspiration for audit quality. Auditors, regulators and investors could ascertain such aspiration from past and current MD&As.Originality/valueThis study associates the manager’s emphasis on audit, measured with computational linguistics from the MD&A, with realized audit quality.

Clinical Characteristics, Patterns of Use, and incidence of Adverse Events in Patients With Nonvalvular Atrial Fibrillation Treated With Oral Anticoagulants in Colombia.

The aim was to analyze the characteristics, treatment patterns, and clinical outcomes of Colombian patients with non-valvular atrial fibrillation (NVAF) under treatment with oral anticoagulants (OAs). Retrospective cohort in patients with NVAF identified from a drug dispensing database, aged ≥18 years, with first prescription of an OA (index) between January/2013 and June/2018, and a follow-up until June/2019. Data from the clinical history, pharmacological variables, and outcomes were searched. International Classification of Diseases-10 codes were used to identify the patient sample and outcomes. Patients were followed until a general composite outcome of effectiveness (thrombotic events), bleeding/safety or persistence (switch/discontinuation of anticoagulant) events. Descriptive and multivariate analyzes (Cox regressions comparing warfarin and direct oral anticoagulants-DOACs) were carried out. A total of 2076 patients with NVAF were included. The 57.0% of patients were women and the mean age was 73.3±10.4 years. Patients were followed for a mean of 2.3±1.6 years. 8.7% received warfarin before the index date. The most frequent OA was rivaroxaban (n=950; 45.8%), followed by warfarin (n=459; 22.1%) and apixaban (n=405; 19.5%). Hypertension was present in 87.5% and diabetes mellitus in 22.6%. The mean CHA2DS2-VASc Score was 3.6±1.5. The 71.0% (n=326/459) of the warfarin patients presented the general composite outcome, and 24.6% of those with DOACs (n=397/1617). The main effectiveness and safety outcomes were stroke (3.1%) and gastrointestinal bleeding (2.0%) respectively. There were no significant differences between patients with warfarin and DOACs regarding thrombotic events (HR: 1.28; 95% CI: 0.68-2.42), but warfarin was associated with higher bleeding/safety events (HR: 4.29; 95% CI: 2.82-6.52) and persistence events (HR: 4.51; 95% CI: 3.81 -5.33). The patients with NVAF in this study were mainly older adults with multiple comorbidities. Compared to warfarin, DOACs were found to be equally effective, but safer and had a lower probability of discontinuation or switch.

Spin-Stand Measurements to Extract the Switching Distributions of Heat-Assisted Magnetic-Recording Media

A new measurement method to characterize the switching temperature distributions of heat-assisted magnetic recording (HAMR) media at recording time scales is presented. The method uses HAMR components in conventional recording systems, such as spin-stand testers and hard disk drives. Using dc noise measurements, a 2-D map of the probability of grains switching is extracted as a function of the medium temperature and of the applied field, which are controlled by the HAMR head laser power and writer current, respectively. These measurements give access to details of the HAMR media temperature and field distributions, as well as provide useful information related to the operation of the HAMR system.

A Selective Bit Dropping and Encoding Co-Strategy in Image Processing for Low-Power Design in DRAM and SRAM

A novel and efficient way of image processing is proposed in this paper, which fully exploits the features of DRAM (Dynamic Random Access Memory) and SRAM (Static Random Access Memory) as well as the human visual system. The proposed strategy first approximates and encodes the image to effectively reduce the number of bit-‘1’ in the original pixel data, then the processed data is pushed into the off-chip DRAM, and later written into the on-chip SRAM for further computation. Since the storage power consumption of DRAM is proportional to the number of bit-‘1’, while the write power consumption of SRAM is linear relative to the switch probability and the square of the supply voltage, fewer bits-‘1’ in the processed pixel data will decrease the power consumption of DRAM and SRAM, yet accompanied by negligible influence on output quality as our proposed method has the advantages of both approximate computation and error compensation. Thus, a tradeoff is finally achieved between storage power consumption and output quality. In the experimental simulations, 39.8% power reduction for DRAM and 25.9% write power reduction for SRAM have been achieved. Regarding output quality, Discrete Cosine Transform (DCT), quantization, inverse quantization and inverse DCT (IDCT) are employed to process the approximated data. The simulations shows average 3.36 dB losses in Peak-Signal-Noise-Ratio (PSNR). Based on this strategy, an approach of priority-based reduction in supply voltage for insignificant pixel data is introduced to achieve further reduction in power consumption for SRAM. Undoubtedly, a lower supply voltage will increase the probability of read error from SRAM. However, with our proposed approximate coding strategy, the output quality is barely impacted by the lower supply voltage.

Zero-State Insert Dual-Layer HAMR Media Recording

Heat-assisted magnetic recording (HAMR) can support extremely high areal densities based on the thermal stability argument. However, significant challenges remain to reduce switching probability distribution (SPD) to improve media SNR. Exchange coupled composite (ECC)-type architectures, such as the designs employed in perpendicular media, are being explored for HAMR media and show potential promise at reducing SPD. In this article, we propose a new approach for the media design that consisting of an exchange decoupled dual-layer HAMR media architecture. In this design, a few net zero magnetization state grains form near the transition resulting in a transition noise reduction when a small difference in a <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">$T_{\text {c}}$ </tex-math></inline-formula> of <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">$\approx 5$ </tex-math></inline-formula> % was applied between the two layers. A geometric 2-D recording model was used to explore this dual-layer media design space and transition noise response. The significant transition noise reduction under the grain size limit condition is attributed to a negative correlation between noise from the top and bottom layers. This simple model was supplemented with micromagnetic recording simulations that verify stable zero-state grains are established near the transition during the recording process. The simulations confirm the significant transition noise reduction, but an increase in the dc noise was observed. Once the dc noise was addressed by increasing the applied field magnitude, a significant SNR gain of 1.4 dB was achieved compared with the equivalent single-layer media.

Power and sample sizes estimation in clinical trials with treatment switching in intention-to-treat analysis: a simulation study

BackgroundTreatment switching, also called crossover, is common in clinical trials because of ethical concerns or other reasons. When it occurs and the primary objective is to identify treatment effects, the most widely used intention-to-treat analysis may lead to underpowered trials. Here, we presented an approach to preview power reductions and to estimate sample sizes required to achieve the desired power when treatment switching occurs in the intention-to-treat analysis.MethodsWe proposed a simulation-based approach and developed an R package to perform power and sample sizes estimation in clinical trials with treatment switching.ResultsWe simulated a number of randomized trials incorporating treatment switching and investigated the impact of the relative effectiveness of the experimental treatment to the control, the switching probability, the switching time, and the deviation between the assumed and the real distributions for the survival time on power reductions and sample sizes estimation. The switching probability and the switching time are key determinants for significant power decreasing and thus sample sizes surging to maintain the desired power. The sample sizes required in randomized trials absence of treatment switching vary from around four-fifths to one-seventh of the sample sizes required in randomized trials allowing treatment switching as the switching probability increases. The power reductions and sample sizes increase with the decrease of switching time.ConclusionsThe simulation-based approach not only provides a preview for power declining but also calculates the required sample size to achieve an expected power in the intention-to-treat analysis when treatment switching occurs. It will provide researchers and clinicians with useful information before randomized controlled trials are conducted.

Measurements of Phase Dynamics in Planar Josephson Junctions and SQUIDs.

We experimentally investigate the stochastic phase dynamics of planar Josephson junctions (JJs) and superconducting quantum interference devices (SQUIDs) defined in epitaxial InAs/Al heterostructures, and characterized by a large ratio of Josephson energy to charging energy. We observe a crossover from a regime of macroscopic quantum tunneling to one of phase diffusion as a function of temperature, where the transition temperature T^{*} is gate-tunable. The switching probability distributions are shown to be consistent with a small shunt capacitance and moderate damping, resulting in a switching current which is a small fraction of the critical current. Phase locking between two JJs leads to a difference in switching current between that of a JJ measured in isolation and that of the same JJ measured in an asymmetric SQUID loop. In the case of the loop, T^{*} is also tuned by a magnetic flux.

An augmented Snake Optimizer for diseases and COVID-19 diagnosis

Feature Selection (FS) techniques extract the most recognizable features for improving the performance of classification methods for medical applications. In this paper, two intelligent wrapper FS approaches based on a new metaheuristic algorithm named the Snake Optimizer (SO) are introduced. The binary SO, called BSO, is built based on an S-shape transform function to handle the binary discrete values in the FS domain. To improve the exploration of the search space by BSO, three evolutionary crossover operators (i.e., one-point crossover, two-point crossover, and uniform crossover) are incorporated and controlled by a switch probability. The two newly developed FS algorithms, BSO and BSO-CV, are implemented and assessed on a real-world COVID-19 dataset and 23 disease benchmark datasets. According to the experimental results, the improved BSO-CV significantly outperformed the standard BSO in terms of accuracy and running time in 17 datasets. Furthermore, it shrinks the COVID-19 dataset’s dimension by 89% as opposed to the BSO’s 79%. Moreover, the adopted operator on BSO-CV improved the balance between exploitation and exploration capabilities in the standard BSO, particularly in searching and converging toward optimal solutions. The BSO-CV was compared against the most recent wrapper-based FS methods; namely, the hyperlearning binary dragonfly algorithm (HLBDA), the binary moth flame optimization with Lévy flight (LBMFO-V3), the coronavirus herd immunity optimizer with greedy crossover operator (CHIO-GC), as well as four filter methods with an accuracy of more than 90% in most benchmark datasets. These optimistic results reveal the great potential of BSO-CV in reliably searching the feature space.

Aspiration drives adaptive switching between two different payoff matrices

Under given social dilemma, different individuals perhaps have different perceptions for the dilemma intensity. Generally speaking, the degree of individual’s perception should be closely related to its ability, the stronger the ability of individual, the weaker the perception for the dilemma intensity will be. On the other hand, the competent individuals may be more likely to carry out altruistic cooperation behavior than those who are relatively lacking in ability. Considering these facts, we introduce an evolutionary game model in which individual can adaptively switch between two payoff matrices with different temptations based on aspiration to explore the cooperation dynamics in spatial prisoner’s dilemma. In this model, two different payoff matrices are denoted by Mw and Ms respectively, the temptation value of the former is small, and the one of the latter is large. For the individual who has adopted Mw to interact, the higher the individual is satisfied with the current payoff, the lower the probability of switching to Ms in the next round, while for the individual who has adopted Ms to interact, the higher the individual is satisfied with the current payoff, the higher the probability of switching to Mw in the next round. Experimental results show that this mechanism of adaptive switching between payoff matrices with different temptations can effectively promote the cooperation of spatial prisoner’s dilemma, and the appropriate aspiration level of individual can provide the most favorable environment for the diffusion of cooperation. The difference in the perception for dilemma intensity will be a new perspective in the study of networked evolution game.

Short-term effect of colorectal cancer on income: analysis of an Italian cohort

IntroductionThe ability to return to work after a cancer diagnosis is a key aspect of cancer survivorship and quality of life. Studies have reported a significant risk of income loss...

A q-binomial extension of the CRR asset pricing model

We propose an extension of the Cox-Ross-Rubinstein (CRR) model based on q-binomial (or Kemp) random walks, with application to default with logistic failure rates. This model allows us to consider time-dependent switching probabilities varying according to a trend parameter on a non-self-similar binomial tree. In particular, it includes tilt and stretch parameters that control increment sizes. Option pricing formulas are written using q-binomial coefficients, and we study the convergence of this model to a Black-Scholes type formula in continuous time. A convergence rate of order is obtained.

Improved PBFT Algorithm Based on Comprehensive Evaluation Model

Blockchain technology is well known due to the advent of Bitcoin. With the development of recent years, blockchain technology has been widely used in medicine, digital currency, energy, etc. The practical Byzantine fault-tolerant (PBFT) algorithm is a consensus algorithm widely used in consortium blockchains. Aiming to address the problems of the PBFT algorithm, low consensus efficiency due to high communication complexity, and malicious behavior of the primary node leading to consensus failure, an improved PBFT algorithm based on a comprehensive evaluation model (TB-PBFT) is proposed. First, nodes are divided into several groups based on the multi-formation control strategy of an unmanned aerial vehicle (UAV) cluster, which significantly reduces the communication complexity. Second, a comprehensive evaluation model combining the entropy method, TOPSIS method, and Borda count is proposed, which uses the behavior of nodes as an evaluation index, and the comprehensive score of nodes is obtained according to the preferences of other nodes. Finally, the highest ranking node is selected as the primary node through the comprehensive evaluation model to ensure the security and stability of the blockchain network. We analyze TB-PBFT algorithms and compare them with other Byzantine fault tolerance algorithms. Theoretical analysis and simulation results show that the TB-PBFT algorithm can improve node scalability and fault tolerance and reduce communication complexity and view switching probability. We also prove that the comprehensive evaluation model can improve the consensus success rate of the algorithm, and the feasibility and effectiveness of the improved consensus algorithm are verified. Hence, it can be applied to the consortium blockchain system effectively and efficiently.

On local convexity in $$\pmb {{\mathbb {L}}^0}$$ and switching probability measures

On local convexity in $$\pmb {{\mathbb {L}}^0}$$ and switching probability measures

COVID-19 and stock returns: Evidence from the Markov switching dependence approach

This paper aims to investigate the regime-switching and time-varying dependence between the COVID-19 pandemic and the US stock markets using a Markov-switching framework. It makes two contributions to the empirical literature by showing that: (a) the variations of the daily reported COVID-19 cases and cumulative COVID-19 deaths induced asymmetric lower (left) and upper (right) tail dependence with the stock markets, and its left and right tail dependence exhibited significant time-varying trends; and (b) the left and right tail dependence between the stock markets and the pandemic exhibited significant regime-switching behaviours, with its switching probabilities in the higher tail dependence stage all being greater than in the lower tail dependence stage after 1 December 2019. Moreover, given that there is concurrent but significant financial market reaction to any unexpected emergence of a transmittable respirational disease or a natural calamity, the outcomes have some vital implications to market players and policymakers.

Monitored anesthesia care and asleep-awake-asleep techniques combined with multiple monitoring for resection of gliomas in eloquent brain areas: a retrospective analysis of 225 patients

BackgroundAwake craniotomy (AC) has become gold standard in surgical resection of gliomas located in eloquent areas. The conscious sedation techniques in AC include both monitored anesthesia care (MAC) and asleep-awake-asleep (AAA). The choice of optimal anesthetic method depends on the preferences of the surgical team (mainly anesthesiologist and neurosurgeon). The aim of this study was to compare the difference in physiological and blood gas data, dosage of different drugs, the probability of switching to endotracheal intubation, and extent of tumor resection and dysfunction after operation between AAA and MAC anesthetic management for resection of gliomas in eloquent brain areas.MethodsTwo-hundred and twenty-five patients with super-tentorial tumor located in eloquent areas underwent AC from 2009 to 2021 in Xijing Hospital. Forty-one patients underwent AAA technique, and the rest one-hundred eighty-four patients underwent MAC technique. Anesthetic management, dosage of different drugs, intraoperative complications, postoperative outcomes, adverse events, extent of resection and motor, and sensory and language dysfunction after operation were compared between MAC and AAA.ResultThere was no significant difference in gender, KPS score, MMSE score, glioma grade, type, and growth site between the patients in the two groups, except the older age of patients in MAC group than that in AAA group. During the whole process of operation, there were greater pulse pressure difference (P = 0.046), shorter operation time (P = 0.039), less dosage of remifentanil (P = 0.000), more dosage of dexmedetomidine (P = 0.013), more use of antiemetics (81%, P = 0.0067), lower use of vasoactive agent (45.1%, P = 0.010), and lower probability of conversion to general anesthesia (GA, P = 0.027) in MAC group than that in AAA group. Blood gas analysis showed that PetCO2 (P = 0.000), Glu concentration (P = 0.000), and PaCO2 (P = 0.000) were higher, but SPO2 (P = 0.002) and PaO2 (P = 0.000) were lower in MAC group than that in AAA group. In the postoperative recovery stage, compared with that of AAA group, the probability of dysfunction in MAC group at 1, 3, 5, and 7 days after operation was lower, which were 27.8% vs 53.6% (P = 0.003), 31% vs 68.3% (P = 0.000), 28.8% vs 63.4% (P = 0.000), and 25.6% vs 58.5% (P = 0.000), respectively.ConclusionCompared with AAA, it seems that MAC has more advantages in the management for resection of gliomas in eloquent brain areas, and MAC combined with multiple monitoring such as cerebral cortical mapping, neuronavigation, and ultrasonic detection is worthy of popularization for the resection of gliomas in eloquent brain areas.

Empirical Investigation of Real Exchange Rate between Pak Rupee and US Dollar Employing Markov Switching-AR Model

This study empirically investigates real exchange rate between Pak Rupee and US Dollaremploying a two state Markov Switching-AR Model. Bai-Perron test for multiple structural breaks foundthree structural breaks in the series. Estimation results of Markov Switching-AR model reveal that if thereal exchange rate is in state one, its probability of staying in same state in the next period is greaterthan 99 percent whereas switching to second state is 0.7 percent. Whereas, if real exchange rate is instate two, its probability of staying to the same state is 99 percent and its probability of switching to stateone in the next period is less than 0.6 percent.

Reversible switching and stability of the epigenetic memory system in bacteria.

In previous work, we have developed a DNA methylation-based epigenetic memory system that operates in Escherichia coli to detect environmental signals, trigger a phenotypic switch of the cells and store the information in DNA methylation. The system is based on the CcrM DNA methyltransferase and a synthetic zinc finger (ZnF4), which binds DNA in a CcrM methylation-dependent manner and functions as a repressor for a ccrM gene expressed together with an egfp reporter gene. Here, we developed a reversible reset for this memory system by adding an increased concentration of ZnSO4 to the bacterial cultivation medium and demonstrate that one bacterial culture could be reversibly switched ON and OFF in several cycles. We show that a previously developed differential equationmodel of the memory system can also describe the new data. Then, we studied the long-term stability of the ON-state of the system over approximately 100 cell divisions showing a gradual loss of ON-state signal starting after 4 days of cultivation that is caused by individual cells switching from an ON- into the OFF-state. Over time, the methylation of the ZnF4-binding sites is not fully maintained leading to an increased OFF switching probability of cells, because stronger binding of ZnF4 to partially demethylated operator sites leads to further reductions in the cellular concentrations of CcrM. These data will support future design to further stabilize the ON-state and enforce the binary switching behaviour of the system. Together with the development of a reversible OFF switch, our new findings strongly increase the capabilities of bacterial epigenetic biosensors.

Well under control: Control demand changes are sufficient for metacontrol.

Metacontrol arises from the efficient retrieval of cognitive control by environmental cues that are predictive of the upcoming control demands. Previous studies have demonstrated that proactive and reactive metacontrol can be indexed by a list-wide switch probability (LWSP) and an item-specific switch probability (ISSP) effect, respectively. However, what triggers metacontrol in the first place has not been clearly articulated. While a "mere-experience" hypothesis attributes metacontrol to changes in control demands, an "affective-signaling" hypothesis suggests that high control demands are aversive and aversiveness drives metacontrol. In two experiments, we adjudicated between these hypotheses by considering the modes of metacontrol (proactive vs. reactive) and temporal dynamics of background valence (sustained vs. transient and positive vs. negative). We induced metacontrol (proactive or reactive) in a task-switching paradigm and created background valence by using positive and negative images as stimuli. With valence being an irrelevant aspect of the task, the design allows us to test whether (task-irrelevant) background valence would modulate metacontrol. While we were able to replicate the LWSP effect in Experiment 1 and the ISSP effect in Experiment 2, we did not find valence modulating either effect, regardless of the background valence being a sustained (Experiment 1) or a transient one (Experiment 2). These findings together suggest that negative valence (i.e., aversiveness) does not necessarily benefit metacontrol, and control demand variations are sufficient to induce metacontrol.

The Account of the Effect of Switch Probability on Switch and Mixing Costs: An ERP Study in a Cued Task-switching Paradigm.

Whether the effect of switch probability on switch and mixing costs is explained by an activation or preparation account is unclear. To investigate the account of the effect of switch probability on switch and mixing costs. We used a cued task-switching paradigm with three switch probabilities (high, 75%; medium, 50%; and low, 25%) with 19 healthy young adults and recorded the cue- and target-locked event-related potentials (ERPs) and behavioral performance. The task included switch and stay trials under high, medium, and low switch conditions, as well as pure trials. There was no significant difference in reaction time (RT) in switch and mixing costs between the high and medium switch conditions. The RT in switch and mixing costs in the high and medium switch conditions was significantly less and more than in the low switch condition, respectively. The cue-locked ERPs revealed significant effects on mixing costs (stay - pure) that were cue early frontal positivity (260-300 ms) in the high and medium switch conditions, and on switch costs (switch - stay) that were cue early central positivity (240-260 ms) in the low switch condition. Moreover, the target-locked ERPs of the mixing costs revealed significant effects on mixing costs that were target P3b (440-540 ms) in all three switch conditions, and on switch costs that were target P3b in the medium and low switch conditions. The effect of switch probability on switch and mixing costs is explained by the activation account.