Uncontrollable Components Research Articles

Intelligent leaching of Zn and Mn from spent disposable batteries to avoid traditional optimizing experiments.

Spent disposable Zn-Mn and Zn-C batteries are important resources for recycling. Acid leaching is the crucial step in the hydrometallurgy process for recycling Zn and Mn from these spent Zn-based batteries. However, to obtain the optimal leaching efficiency, the uncontrollable components in waste feed and various leaching parameters cause numerous replicated optimal experiments, increasing the recovery cost and environmental risks. To solve the issues, we employed machine learning (ML) techniques to construct models to predict Zn and Mn leaching from spent disposable batteries without optimizing experiments. Among four ML algorithms tested, the extreme gradient boosting demonstrated superior predictive performance, achieving an R2 of 0.85-0.98 across the training, test, and verification datasets. An analysis of feature importance indicated that the particle size, waste composition, acid concentration, temperature, and time affected the metal leaching most. This study also revealed the interaction effects of the waste properties and leaching process on the metal leaching. Furthermore, we created a user-friendly graphical user interface (GUI) that enables quick acquisition of metal leaching results, requiring only the measurement of waste particle size and component. Finally, experimental verification confirmed the practicability of the GUI. This study achieves intelligent metal leaching from spent batteries and overcomes the high recovery cost and environmental risks associated with traditional experimental optimizing methods.

Intelligent leaching rare earth elements from waste fluorescent lamps.

Rare earth elements (REEs), one of the global key strategic resources, are widely applied in electronic information and national defense, etc. The sharply increasing demand for REEs leads to their overexploitation and environmental pollution. Recycling REEs from their second resources such as waste fluorescent lamps (WFLs) is a win-win strategy for REEs resource utilization and environmental production. Pyrometallurgy pretreatment combined with acid leaching is proven as an efficient approach to recycling REEs from WFLs. Unfortunately, due to the uncontrollable components of wastes, many trials were required to obtain the optimal parameters, leading to a high cost of recovery and new environmental risks. This study applied machine learning (ML) to build models for assisting the leaching of six REEs (Tb, Y, Eu, La, and Gd) from WFLs, only needing the measurement of particle size and composition of the waste feed. The feature importance analysis of 40 input features demonstrated that the particle size, Mg, Al, Fe, Sr, Ca, Ba, and Sb content in the waste feed, the pyrometallurgical and leaching parameters have important effects on REEs leaching. Furthermore, their influence rules on different REEs leaching were revealed. Finally, some verification experiments were also conducted to demonstrate the reliability and practicality of the model. This study can quickly get the optimal parameters and leaching efficiency for REEs without extensive optimization experiments, which significantly reduces the recovery cost and environmental risks. Our work carves a path for the intelligent recycling of strategic REEs from waste.

Application of machine learning to guide efficient metal leaching from spent lithium-ion batteries and comprehensively reveal the process parameter influences

Recycling spent lithium-ion batteries (LIBs) has been a global hot spot due to the increasing scrap amount and enriching valuable resources. Acid leaching is the crucial step of hydrometallurgy recycling metals from spent LIB. However, the uncontrollable components cause many trials for obtaining the optimal leaching parameters, which increases the recycling cost and environmental risk. Herein, this study applied machine learning (ML) to guide metal leaching from spent LIBs and could quickly obtain the leaching results without the vast leaching experiments. After referring to the relative studies between 2005 and 2022, a total of 17,588 data points were collected as the dataset for ML. The process parameter influences of metal leaching were comprehensively revealed through the ML analysis of 20 input features and 4 output metal leaching efficiency. Then, a convenient graphical user interface (GUI) was developed to guide efficient metal leaching from spent LIBs, only measuring the particle size and composition of waste and avoiding extensive leaching experiments. Finally, some experiments verified the GUI reliability. This study can significantly reduce the experiment cost and environmental risk, which trailblazes the smart and efficient recycling of spent LIBs.

Стан наукової проблеми щодо дослідження характеристик продуктів взаємодії розплаву ядерного палива з бетоном

Стан наукової проблеми щодо дослідження характеристик продуктів взаємодії розплаву ядерного палива з бетоном

MULTICHANNEL THEORY OF RECEIVING ANTENNAS

Scattering field of an arbitrary receiving antenna can be considered as the sum of the information component of the scattering field and the orthogonal component. Each of them consists of a main and an additional component. These components form interaction channels through which power is taken from the plane wave by the receiving antenna. This work is devoted to the study of the connection between the components of the information component of the scattering field and the orthogonal component of the scattering field of the receiving antenna with the wave incident on it. It is shown that additional components of the information component of the scattering field create interaction channels through which power is taken from the plane wave, spent only on the formation of mutual power between the main and additional components of the information component of the scattering field, and the power transmitted from the plane wave to the antenna load is not taken. The power supplied to the antenna load is transmitted only through the interaction channel of the main information component of the scattering field. In turn, the powers of the controlled and uncontrolled components of the information component of the scattering field are created due to the power selected through the channels of the main information and orthogonal components of the scattering field.

Skin Barrier in Patients with Lichen Simplex Chronicus in the conditions of A COVID-19 Pandemic

Background: The primary role of the skin is to protect the body from environmental factors. The intact skin is a barrier to the uncontrolled water loss, proteins and plasma components from the organism. Frequent hand and body wash has a negative impact on skin ecosystem by removing lipids which naturally preserve and protect it. Objective: The purpose of this study is to evaluate changes in barrier functions of skin in the condition of repeated body and hand wash in Lichen Simplex Chronicus (LSH) patients. Materials and Methods: Transepidermal Water Loss (TEWL) and Hydratation (H) of epidermis in healthy and damaged skin were measured in 36 non-hospitalized LSH patients. The results were compared with those from a similar study but in patients before the COVID pandemic recommended hygiene regimen. Results: The results reported in the present study showed significantly more pronounced skin barrier disorders compared to those announced in LSH patients before the COVID pandemic. Conclusion: All the reported and analyzed results indicate that disorders of skin barrier are connected with severity and duration of LSH. The frequent washing regime act as an additional reduction of the barrier function of the skin and thus worsens the parameters of the disease.

Decomposed Modeling of Controllable and Uncontrollable Components in Power Systems with High Penetration of Renewable Energies

The high penetration of variable renewable energies requires the flexibility from both the generation and demand sides. This raises the necessity of modeling stochastic and flexible energy resources in power system operation. However, some distributed energy resources have both stochasticity and flexibility, e.g., prosumers with distributed photovoltaics and energy storage, and plug-in electric vehicles with stochastic charging behavior and demand response capability. Such partly controllable participants pose challenges to modeling the aggregate behavior of large numbers of entities in power system operation. This paper proposes a new perspective on the aggregate modeling of such energy resources in power system operation. Specifically, a unified controllability-uncontrollability-decomposed model for various energy resources is established by modeling the controllable and uncontrollable parts of energy resources separately. Such decomposition enables the straightforward aggregate modeling of massive energy resources with different controllabilities by integrating their controllable components with linking constraints and uncontrollable components with dependent discrete convolution. Furthermore, a two-stage stochastic unit commitment model based on the proposed model for power system operation is established. The proposed model is tested using a three-bus system and real Qinghai provincial power grid of China. The result shows that this model is able to characterize at high accuracy the aggregate behavior of massive energy resources with different levels of controllability so that their flexibility can be fully explored.

Deliberate evasion of narcotic legislation: Trends visualized in commercial mixtures of new psychoactive substances analyzed by GC-solid deposition-FTIR

List-based approaches for judicial control of synthetic drugs inevitably introduce a group of legal highs that do not fall under the scope of legislation but may exhibit similar effects and associated health risks as illicit substances. Differences between controlled and uncontrolled components may be as minor as a single molecular group rearrangement. This phenomenon complicated forensic drug analysis in recent years due to both the rise of new psychoactive substances (NPS), and selectivity limitations of the workhorse gas chromatography-mass spectrometry (GC−MS) technique, especially with respect to ring-isomers. Our study demonstrates the value of GC-solid deposition-Fourier-transform infrared spectroscopy (FTIR) as a complementary technique for NPS identification in multi-drug mixtures. The instrument design using direct deposition of the GC effluent on a cryogenically cooled ZnSe-disk allows for signal enhancement of minor constituents by collecting eluting peaks of multiple GC injections. Highly diagnostic spectra were obtained for all ortho, meta and para-isomers of fluoroamphetamine (FA), fluoromethamphetamine (FMA), methylmethcathinone (MMC) and methylethcathinone (MEC). Combined results of GC−MS and GC-solid deposition-FTIR revealed the presence of up to 11 individual NPS mixed together in liquid samples sold as research chemicals or room odorizer in The Netherlands. Sample compositions rapidly evolved over time with recently controlled substances such as 4-fluoroamphetamine (4-FA), pentedrone, ethylone and 4-methylethcathinone (4-MEC) being replaced by uncontrolled isomers or analogues as 2-fluoroamphetamine (2-FA), 2- or 4-fluoromethamphetamine (2-FMA, 4-FMA) and dimethylone. In 12 different samples all marketed under two brand names, a total of 9 different compositions were identified in samples from 2018 and 2019.

Can spatial filtering separate voluntary and involuntary components in children with dyskinetic cerebral palsy?

The design of myocontrolled devices faces particular challenges in children with dyskinetic cerebral palsy because the electromyographic signal for control contains both voluntary and involuntary components. We hypothesized that voluntary and involuntary components of movements would be uncorrelated and thus detectable as different synergistic patterns of muscle activity, and that removal of the involuntary components would improve online EMG-based control. Therefore, we performed a synergy-based decomposition of EMG-guided movements, and evaluated which components were most controllable using a Fitts' Law task. Similarly, we also tested which muscles were most controllable. We then tested whether removing the uncontrollable components or muscles improved overall function in terms of movement time, success rate, and throughput. We found that removal of less controllable components or muscles did not improve EMG control performance, and in many cases worsened performance. These results suggest that abnormal movement in dyskinetic CP is consistent with a pervasive distortion of voluntary movement rather than a superposition of separable voluntary and involuntary components of movement.

The Atrial fibrillation Better Care (ABC) pathway is associated to a lower incidence of cardiac complications in patients with atrial fibrillation: a report from the ATHERO-AF study

Abstract Background The integrated management of atrial fibrillation (AF) patients according to the Atrial fibrillation Better Care (ABC, A, Avoid stroke with anticoagulation; B, better symptom management; C, Cardiovascular and comorbidity risk management) pathway has associated with a reduced incidence of thromboembolic events and mortality. However, whether this approach also results in a lower rate of cardiac complications is unknown. Purpose To investigate the rate of major adverse cardiovascular events (MACE) in AF patients according to compliance with the ABC pathway. Methods This prospective single-center cohort study included 1157 patients with nonvalvular AF from the ATHERO-AF study. The A, B, and C groups were defined as follows: “A” by a Time in Therapeutic Range ≥70% in vitamin K antagonists-treated patients or appropriate dose for patients on direct oral anticoagulants; “B” by a European Heart Rhythm Association (EHRA) symptom scale I-II (vs. III-IV), and “C” as optimized cardiovascular comorbidity management (i.e. use of ACE inhibitors in heart failure patients, blood pressure <140/90, use of statins and beta blockers in patients with prior ischemic heart disease). The primary end point was a composite of MACE including fatal/non-fatal myocardial infarction, coronary revascularization and cardiovascular death (progressive heart failure, sudden cardiac death and procedure-related death). Results Overall, 458 (39.6%) patients were optimally managed according to the ABC (ABC-compliant group), while the remaining 729 patients presented at least one uncontrolled component (ABC non-compliant group). During a mean follow up of 35 months, (2688 patient-years), 64 MACE were recorded 2.38%/year. Kaplan Meier curve analysis showed a significant higher rate of MACE in ABC non-compliant group compared to the ABC-compliant (54 and 10 MACE in each group, respectively, log-rank test p=0.006, figure). The risk of MACE increased by the number of uncontrolled ABC components: Hazard ratio HR) for 1 component 1.697, 95% Confidence Interval 95% CI 0.814–3.537, p=0.158; HR for 2 components 4.157, 95% CI 1.994–8.665, p<0.001); HR for 3 components 5.100, 95% CI 1.596–16.295, p=0.006. ABC non-compliant group remained associated with an increased risk of MACE using Cox proportional hazard regression analysis (HR 2.175, 95% CI 1.098–4.309, p=0.026) after adjustment for CHA2DS2VASc score, antiplatelet drugs and digoxin use. Conclusion The majority of AF patients is not currently optimally managed. An integrated care ABC approach is associated with a reduced risk of MACE in the AF population. Figure 1. Kaplan-Meier curves Funding Acknowledgement Type of funding source: None

Towards Characterization of Indoor Environment in Smart Buildings: Modelling PMV Index Using Neural Network with One Hidden Layer

Modelling of comfort with the use of neural networks in modern times has become extremely popular. In recent years, scientists have been using these methods because of their satisfactory accuracy. The article proposes a method of modelling feedforward neural networks, thanks to which it is possible to obtain the most efficient network with one hidden layer in terms of a given quality criterion. The article also presents the methodology for modelling a PMV index, on the basis of which it can be demonstrated whether the network will work properly not only on paper but in reality as well. The objective of this work is to develop a performance model allowing the effective improvement of all electrical and mechanical devices affecting the energy efficiency and indoor environment in smart buildings. To achieve this, several attributes of indoor environment are included, namely: air leakage as a connection to the outdoor environment, but also as uncontrolled component of energy, ventilation as delivery and distribution of fresh air in the building space, individual ventilation on demand indoor air quality (IAQ) in the dwelling or as a personal IAQ control, source control of pollutants in the building, thermal comfort, temperature, air movement and humidity control (humidity modifiers, i.e., buffers different from the air conditioning radiation from cold and hot surfaces bringing forward a question about the strategy of the process control. One may either develop a series of control models to be synthesized later or one can use one over-arching characteristic and use its components for operating the control system. The paper addresses the second strategy and uses the concept of PMV for a criterion of broadly defined thermal comfort (including ventilation and air quality).

Gun Ownership and Self‐Serving Attributions for Mass Shooting Tragedies*

ObjectiveIndividuals develop causal narratives that help explain events, behaviors, and conditions. Individuals ascribe events and behaviors to controllable components, such as individual choice, or uncontrollable components, such as broader forces in the environment. We join attribution theory with motivated reasoning and outline how gun ownership structures perceptions of mass shootings and subsequent blame.MethodsUsing individual‐level data from national surveys we examine the connection between causal attributions for mass shootings and gun ownership.ResultsOur findings suggest that firearm possession engenders self‐serving attributions about the causes of gun violence and resists calls for policy changes after mass shooting.ConclusionGiven the significant proportion of citizens who own guns, the prospect for policy changes that address gun‐related causes of mass shootings is unlikely.

“Nanny State” Politics: Causal Attributions About Obesity and Support for Regulation

We posit that individuals develop causal stories to explain the world around them, including events, behaviors, and conditions in society. These are narratives that attribute causes to controllable components, such as individual choices, or uncontrollable components, such as broader forces in the environment. We use attribution theory to understand how group identity and individual characteristics may shape causal attributions about obesity. Based on previous empirical findings, we argue that attributions and identity can explain policy preferences. We test our hypotheses using individual-level data from a unique national survey of American adults. Our findings suggest that partisan and weight identities predispose people to make certain attributions about obesity, and these attributions influence policy preferences related to obesity. We suggest policymakers need to consider public attributions about obesity and future research should develop more refined measures of attributions.

Spending Carveouts Substantially Improve the Accuracy of Performance Measurement in Shared Savings Arrangements: Findings From Simulation Analysis of Medicaid ACOs.

Accuracy of spending-based provider performance metrics is limited by random variation and components of spending that are uncontrollable by providers. Such components vary according to the care management focus and operational maturity of each provider group. This study uses data from New Jersey Medicaid accountable care organizations (ACOs) to examine how carving out uncontrollable components of spending affects the accuracy of performance measures in shared savings arrangements. Spending on injury care, custodial care in facilities (CCF), and amounts above $100 000 per patient are used as examples of potentially uncontrollable spending. Data from 7 applicant Medicaid ACOs are used to conduct Monte Carlo simulations examining the effects of carving out each type of uncontrollable spending under the assumption that controllable spending is reduced by 5%. The simulations show that failure to carve out uncontrollable injury care spending adds −3 to +1 percentage points of bias to the measurement of the true average savings rate (ASR) of 5% and can increase mean squared error (MSE) by a factor of up to 3. Failure to carve out uncontrollable CCF spending generates bias ranging from −4 to +9 percentage points and increases MSE by factors of 8 or more. Failure to carve out uncontrollable spending above $100 000 per person generates bias ranging from −5 to +5 percentage points and increases MSE by factors of 13 or more. Compared with the main modeling reported above, sensitivity analyses find even greater distortions in measured performance when uncontrollable spending is not carved out of the ASR calculation.

A Three-Component Model Based on Macropropagation Phenomena Approach for Complex Building Scattering

Multipaths represent a common predominant and uncontrolled component on channel impairments for all terrestrial and Land Mobile Satellite systems. Without restrictions w.r.t mobile terrestrial applications, the addressed multipath problematic in this paper is focused on Land Mobile Satellite applications where delayed signal replicas are highly impacting performances on communication systems while they induce strong positioning errors for navigation systems. The actual trend in propagation channel modelling is to improve the multipath characterisation and representation by using semideterministic and hybrid physical-statistical models into channel simulators instead of narrow-band empirical approaches. In this context, this paper presents a new simplified model, called 3CM (3-Component Model) to reproduce building scattering in an efficient way which strongly improves computation performances. This model is based on asymptotic methods, namely, PO (Physical Optics) which allows the 3CM to be frequency scalable, polarimetric, and dielectric materials oriented. Note that the proposed model and the retained approach can be integrated into more complex tools such as existing ray tracers. However, this issue is not discussed in this paper.

Convex Integration and Infinitely Many Weak Solutions to the Perona--Malik Equation in All Dimensions

We prove that for all smooth nonconstant initial data the initial-Neumann boundary value problem for the Perona--Malik equation in image processing possesses infinitely many Lipschitz weak solutions on smooth bounded convex domains in all dimensions. Such existence results have not been known except for the one-dimensional problems. Our approach is motivated by reformulating the Perona--Malik equation as a nonhomogeneous partial differential inclusion with linear constraint but some uncontrollable components of gradient. We establish a general existence result by a suitable Baire category method under a pivotal density hypothesis. We finally fulfill this density hypothesis by convex integration based on certain approximations from an explicit formula of lamination convex hull of some matrix set involved.

Efficient robust control of first order scalar conservation laws using semi-analytical solutions

This article presents a new robust control framework for transportation problems in which the state is modeled by a first order scalar conservation law. Using an equivalent formulation based on a Hamilton-Jacobi equation, we pose the problem of controlling the state of the system on a network link, using initial density control and boundary flow control, as a Linear Program. We then show that this framework can be extended to arbitrary control problems involving the control of subsets of the initial and boundary conditions. Unlike many previously investigated transportation control schemes, this method yields a globally optimal solution and is capable of handling shocks (i.e. discontinuities in the state of the system). We also demonstrate that the same framework can handle robust control problems, in which the uncontrollable components of the initial and boundary conditions are encoded in intervals on the right hand side of inequalities in the linear program. The lower bound of the interval which defines the smallest feasible solution set is used to solve the robust LP/MILP. Since this framework leverages the intrinsic properties of the Hamilton-Jacobi equation used to model the state of the system, it is extremely fast. Several examples are given to demonstrate the performance of the robust control solution and the trade-off between the robustness and the optimality.

Patients With Uncontrolled Components of Metabolic Syndrome Have Increased Risk of Complications Following Total Joint Arthroplasty

Metabolic syndrome (MetS)–a diagnostic grouping of diabetes, dyslipidemia, hypertension, and obesity–has been indicated as a risk factor for perioperative complications following total joint arthroplasty (TJA). This study investigates the impact of MetS on perioperative complications, specifically the importance of controlling MetS components. One hundred thirty-three patients undergoing TJA with all four components of MetS were identified. They were matched one-to-one with patients without MetS. Control of diabetes, dyslipidemia, and hypertension was assessed. Thirty-five patients with MetS were found to have at least a single uncontrolled component. The complication rates were 49%, 8%, and 8% for uncontrolled MetS, controlled MetS, and no MetS, respectively. Multivariate analysis confirmed independent associations between control of MetS components and both perioperative complications and length of stay. Both surgeons and patients should be aware of the substantial risk of dangerous complications following TJA in patients with uncontrolled metabolic syndrome.

A Combined Trauma Model of Chest and Abdominal Trauma With Hemorrhagic Shock—Description of a New Porcine Model

Despite the high incidence and prognostic relevance of hemorrhagic shock and abdominal and blunt chest trauma in multiply injured patients, there are no animal models combining these injuries. Therefore, we established a new porcine multiple trauma model consisting of blunt chest trauma, penetrating abdominal trauma (two incisions in the right upper liver lobe using a four-edged scalpel and subsequent liver packing), and pressure-controlled hemorrhagic shock with a mean arterial pressure of 30 ± 5 mmHg (a maximum of 45% of the total blood volume). The combined traumatic insult led to severe signs of hemorrhagic shock and impaired pulmonary function. In conclusion, a consistent, reproducible, and clinically relevant porcine model of multisystem injury with controlled (pressure-controlled blood withdrawal) and uncontrolled components of hemorrhage (liver laceration) with the potential for rebleeding was established.

Temporal Properties of Liquid Crystal Displays: Implications for Vision Science Experiments

Liquid crystal displays (LCD) are currently replacing the previously dominant cathode ray tubes (CRT) in most vision science applications. While the properties of the CRT technology are widely known among vision scientists, the photometric and temporal properties of LCDs are unfamiliar to many practitioners. We provide the essential theory, present measurements to assess the temporal properties of different LCD panel types, and identify the main determinants of the photometric output. Our measurements demonstrate that the specifications of the manufacturers are insufficient for proper display selection and control for most purposes. Furthermore, we show how several novel display technologies developed to improve fast transitions or the appearance of moving objects may be accompanied by side–effects in some areas of vision research. Finally, we unveil a number of surprising technical deficiencies. The use of LCDs may cause problems in several areas in vision science. Aside from the well–known issue of motion blur, the main problems are the lack of reliable and precise onsets and offsets of displayed stimuli, several undesirable and uncontrolled components of the photometric output, and input lags which make LCDs problematic for real–time applications. As a result, LCDs require extensive individual measurements prior to applications in vision science.