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Observability of a hybrid system is defined as the ability to determine the continuous state of the system. Whether a hybrid system is observable or not depends on which events can be disabled, which events can be forced, and the connectivity of the discrete states, as well as its continuous dynamics. We model a hybrid system using a hybrid machine that takes into consideration both continuous variables and discrete events. We classify hybrid systems into four classes based on their discrete-event parts. For each class, conditions are derived to check observability. If a hybrid system is not observable, then we check if a weaker version of observability, called B-observability, is satisfied. B-observability requires that a hybrid system become observable after some finite occurrences of events. Conditions are derived to check B-observability. These conditions involve both the discrete-event and continuous-variable parts of hybrid systems. If the continuous-variable part of a system has a constant A matrix, then the conditions for the continuous-variable part can be simplified. We illustrate the results by an example of a battery management system of an electric vehicle.

Neoantigens play a crucial role in cancer immunotherapy. However, the effectiveness and safety of neoantigen-based immunotherapies in patients with colorectal cancer (CRC), particularly in the Chinese population, have not been well studied. This study explored the feasibility and effectiveness of neoantigens in the treatment of CRC. Whole-exome sequencing (WES) and transcriptome sequencing were used to identify somatic mutations, RNA expression, and human leukocyte antigen (HLA) alleles. Neoantigen candidates were predicted, and immunogenicity was assessed. The neoantigens TSHZ3-L523P, RARA-R83H, TP53-R248W, EYA2-V333I, and NRAS-G12D from Patient 4 (PW4); TASP1-P161L, RAP1GAP-S215R, MOSPD1-V63I, and NAV2-D1973N from Patient 10 (PW10); and HAVCR2-F39V, SEC11A-R11L, SMPDL3B-T452M, LRFN3-R118Q, and ULK1-S248L from Patient 11 (HLA-A0201

TANK-binding kinase1 (TBK1) haploinsufficiency has been shown to cause both amyotrophic lateral sclerosis (ALS) and frontotemporal dementia (FTD); however, the mechanism is unclear. Myeloid Tbk1 knockout mice (Tbk1-LKO mice) were established and motor function and pathological analyses were also performed. The level of p-TBK1 was analyzed in the ALS animal model and in patient samples using flow cytometry. The expression of inflammatory proteins and mRNAs was analyzed via western blotting and RT-PCR, respectively. The latency to fall in seven-month-old Tbk1-LKO mice was significantly reduced in evaluations conducted on two consecutive days. Overall, 25.6% of Tbk1-LKO mice presented paralysis symptoms and signs, along with a loosened myelin sheath and axon degeneration at 14–16 months of age. Furthermore, the Tbk1 deficiency in myeloid cells induced inflammatory cell infiltration and dysbacteriosis in the digestive tract. Additionally, p-TBK1 levels were reduced by 29.5% and 14.8% in monocytes of patients with definite ALS and probable ALS and decreased by 27.6% and 45.5% in monocytes and microglia of ALS animals, respectively. The use of PEI-mannose-TBK1 or PEI-mannose-SaCas9-sgRNA to delete mutant SOD1 in macrophages significantly delayed disease onset and prolonged survival in the mouse model of ALS. Based on these data, inflammatory monocyte and macrophage infiltration and impaired innate immune defenses contribute to ALS and FTD.

Drug delivery systems demonstrate how the pharmaceutical product is administered to the target site to provide therapeutic action. Nowadays, there are a growing number of fungi causing diseases worldwide. These infections can be grouped into four, which are superficial mycosis, cutaneous mycosis, subcutaneous mycosis and systemic mycosis. Researchers believe that solely dependent on presently available antifungal compounds would not be sufficient to treat these mycoses. Introduction of a whole new antifungal drug acting to the target sites must undergo a long process of discovery, various clinical testing and trials on animals and human, development and regulatory approval then finally brought to the market. It is tedious, big-budget and has a high probability of failure. Hence, concurrently, modifications of the existing drug delivery system have never left out and are being pursued innovatively. Applying the knowledge in pharmacodynamics and pharmacokinetic principles, novel advances in antifungal drug delivery systems have been developed and managed to conquer the issues of solubility, stability, bioavailability, safety and effectiveness present in conventional formulations and methods of administration. Vesicular system, nano-particulate based system, colloidal carriers and the miscellaneous drug delivery system are the four major groups of advances in delivering antifungal drugs. The established therapeutic agents for antifungal therapy such as Amphotericin B and azole types can be formulated into different carriers and delivery systems that specifically target the infected area and the illness level of the patient. Novel antifungal drug delivery systems have opened a new dimension in minimising the adverse effects of drugs. Key words: Fungal infections, Antifungal drugs, Novel delivery.

Distributed algorithms have been proposed as options to scale control propositions to the massive number of intelligent energy devices, sub-systems, and distributed energy resources being integrated into the electricity grid. Distributed algorithms rely on the communication network for exchanging information. Failures in the communication network can jeopardize distributed decision-making and in the worst-case scenario can lead to system-level stability problems. This paper proposes a communication-failure-resilient architecture for distributed operation and control in smart grids with hybrid producer/consumer (prosumer) agents. We describe the relations between system-wide performance and communication failures and identify topological conditions on the cyber-physical network, under which prosumers can perform key operating tasks, such as distributed frequency regulation through an imperfect communication network.

Background: Shufeng Jiedu capsule has been widely used in China for acute upper respiratory tract infections (AURTIs). The aim of this study was to evaluate its effectiveness and safety for AURTIs.Methods: Randomized controlled trials comparing SFJD with conventional drug for patients with AURTIs were included. Eight databases were searched from their inceptions to February 2021. Data was synthesized using risk ration (RR) or mean difference (MD) with their 95% confidence interval (CI). The primary outcome was resolution time of typical symptoms.Results: Twenty-five RCTs involving 3410 patients were included. SFJD in combination with conventional drug was associated with; in common cold shortening the duration of fever (MD −1.54 days, 95% CI [−2.15,−0.92], I2 = 80%, n = 385, 3 trials) and cough (MD −1.22 days, 95% CI [−1.52, −0.93]); in herpangina, shortening the duration of fever (MD -0.68 days, 95% CI [−1.15, −0.21], I2 = 68%, n = 140, 2 trials) and blistering (MD −0.99 days, 95% CI [−1.23, −0.76], n = 386, 3 trials); in acute tonsillitis and acute pharyngitis shortening the duration of fever (MD −1.13 days, 95% CI [−1.36, −0.90], I2 = 33%, n = 688, 7 trials) and sore throat (MD −1.13 days, 95% CI [−1.40, −0.86], I2 = 84.1%, n = 1194, 10 trials). SFJD also improving their cure rate with a range (1–5 days). No serious adverse events were reported.Conclusion: Low certainty evidence suggests that SFJD appears to shorten the duration of symptoms in AURTIs, improve cure rate and seems safe for application. However, high quality placebo controlled trials are warranted to confirm its benefit.

Pediatric patients with short bowel syndrome (SBS) are at risk of developing small intestinal bacterial overgrowth (SIBO). Prevention of SIBO using cyclic enteric antibiotics has been implemented to control the balance in microbial ecosystems, although its effectiveness has not been well studied. This study aimed to explore the change in the gut microbial composition in SBS patients during cyclic antibiotic phases and antibiotic-free period, and to compare the microbiota composition between healthy controls and SBS patients. SBS patients taking oral metronidazole alternating with trimethoprim–sulfamethoxazole (TMP–SMT) and antibiotic-free conditions as a ‘10-day cyclic protocol’ were involved in fecal microbiome study using Illumina 16S sequencing. When healthy control possessed the majority of Bacteroidetes spp. (54%) and Firmicutes spp. (33%), the microbial composition in SBS patients especially Firmicutes spp. and Proteobacteria spp. was prominently changed in each phase of treatment. In antibiotic-free period, SBS patients displayed 49% Firmicutes and 36% Proteobacteria. However, higher Proteobacteria than Firmicutes were detected at the commencement of metronidazole (58% versus 33%). Similarly, 56% Proteobacteria and 27% Firmicutes were found during TMP–SMT. Escherichia coli increased prominently during the antibiotic periods. Prophylactic antibiotics change the gut microbiota composition in an unfavorable direction, especially when repeatedly used for a long period. This practice should be reconsidered. III.

The aim of this study was to explore the lived experiences of interprofessional collaboration among nurses, doctors, and respiratory therapists during medical emergencies in the intensive care unit.Descriptive phenomenological study.Participants will be recruited through purposive sampling with maximum variation across the ICUs in a tertiary hospital in Singapore. Guided by data saturation, data collection will include individual semi-structured interviews with ICU nurses, physicians, and respiratory therapist who have attended to medical emergencies such as cardiopulmonary arrest or difficult airway management in the ICUs. Interviews will be audio recorded, transcribed verbatim, and analysed via Colaizzi's descriptive phenomenology method. Research Ethics Committee approval was sought from the National Healthcare Group, Domain Specific Review Board (April 2019). The study is funded by the National Healthcare Group - Health Outcomes and Medical Education Research Grant (April 2019). The study is expected to be concluded by April 2020.Whilst interprofessional collaboration remains a major interest among nursing research, there is a paucity of evidence surrounding interprofessional collaboration in the specific context of medical emergencies in the ICUs. This is especially crucial as the failure of interprofessional collaboration during medical emergencies can be catastrophic to patient safety. Hence, this study will adopt a qualitative approach to contribute to the evidence base surrounding this lesser known phenomenon. The findings generated from this study will inform future team training initiatives, advance nursing leadership initiatives, and identify barriers and facilitators towards fostering greater interprofessional collaboration during medical emergencies.The evidence gained from this study contributes to the limited knowledge base of interprofessional collaboration during medical emergencies. Findings will have vast impact on nursing and interprofessional programs such as crisis leadership and management. The findings could also inform practice frameworks during medical emergencies to support interprofessional collaboration and optimize patient care.目的: 本研究旨在探讨在重症监护病房医疗紧急情况下护士、医生和呼吸治疗师之间的专业间合作的现实经历。 设计: 描述性现象学研究。 方法: 在新加坡三级医院的重症监护病房中通过有目的抽样尽可能多地招募参与者。受实现数据饱和目标的引领,数据收集将包括对重症监护病房护士、内科医生和呼吸治疗师进行个人半结构式访谈。因为他们曾在重症监护病房处理过紧急医疗事件,如心肺骤停和气道管理困难。访谈将被录音,然后逐字转录,并采用Colaizzi的描述现象学方法进行分析。研究伦理委员会经过国家卫生保健集团特定领域审查委员会(2019年4月)批准。此研究由国家医疗保健集团-健康结果和医学教育研究提供资金支持(2019年4月)。这项研究预计将于2020年4月完成。 讨论: 虽然跨专业合作仍然是护理研究的一个主要兴趣领域,但是目前在重症监护病房的医疗紧急情况的特定背景下的有关跨专业合作的证据非常缺乏。这一点非常关键,因为在医疗紧急情况下,跨专业合作的失败可能对病人的生命造成灾难性影响。因此,本研究将采用定性的方法来为这一鲜为人知的现象提供证据基础。这项研究的结果将为未来的团队培训计划提供信息,推进护理领导计划,并确定在医疗紧急情况下识别障碍和促进更大的专业间合作。 影响: 从研究中获得的证据将有助于扩大有限的医疗紧急情况下专业间合作知识库。研究结果将对护理和诸如危机领导和管理等跨专业合作项目产生巨大影响。研究结果还可以为医疗紧急情况下的实践框架提供信息,以支持专业间的协作和优化患者护理。.

This paper is concerned with distributed energy management and control issues of both generators and loads. It aims to maximize the total social welfare that balances generation-side expanses, user-side payments, and transmission line costs. A distributed control strategy with continuous information exchange among neighbors is first proposed. It is shown that this distributed algorithm achieves the global optimal power outputs on generators and the optimal electricity usage on loads asymptotically. To reduce communication resource consumptions, the distributed optimization algorithm is further expanded to incorporate event-triggered communication and control mechanism. In this new algorithm, an event-triggering condition for each generator and each load is employed to determine when its related state information should be sampled and transmitted to its neighbors. Compared with the standard periodic sampling and communication schemes, this new distributed and event-triggered algorithm can significantly reduce communication data flows while achieving the nearly identical control performance to that under continuous data communications. The theoretical results of this paper are validated by using a simulation case study with distributed generators and multiple loads on an IEEE 9-bus system.

Huanglian-Renshen-Decoction (HRD) is widely used to treat type 2 diabetes mellitus (T2DM) in China. However, the underlying mechanism is unclear. We aimed to investigate the mechanism by which HRD regulates the glucose level. Forty 7-8-week-old db/db (BSK) mice were randomly assigned to the following four groups: model, low dose HRD (LHRD), high dose HRD (HHRD), and saxagliptin (SAX). Additionally, 10 db/m mice were assigned to control group. The experimental mice were administered 3.03g/kg/d and 6.06g/kg/d of HRD in the LHRD and HHRD groups, respectively, and 10mg/kg/d saxagliptin in the SAX group for 8 weeks. The control and model groups were supplied with distilled water. After the intervention, the pancreas and blood were collected and tested. Compared with that of model group, the fasting blood glucose (FBG) was significantly decreased in all intervention groups (p < 0.05 or 0.01), whereas fasting serum insulin (FINS) was increased significantly in both HHRD and SAX groups. The immunofluorescence images showed that the mass of insulin+ cells was increased and that of glucagon+ cells was reduced obviously in experimental groups compared to those of the model group. In addition, the coexpression of insulin, glucagon, and PDX1 was decreased in HHRD group, and the level of caspase 12 in islet was decreased significantly in all intervention groups. However, little difference was found in the number and morphology of islet, and the expression of ki67, bcl2, bax, caspase 3, and cleaved-caspase 3 in the pancreas among groups. Interestingly, the cleaved-Notch1 level was increased and the Ngn3 level in islet was decreased significantly in HHRD group. The HRD showed dose-dependent effects on glucose metabolism improvement through maintenance of β cell identity via a mechanism that might involve the Notch1/Ngn3 signal pathway in db/db mice.

What is known and objective The benefits of local infiltration analgesia (LIA) in knee arthroplasty (KA) have been well-documented. However, it is unknown whether adding a corticosteroid to the composition of the LIA is beneficial. This study aimed to investigate the efficacy and safety of administering periarticular steroids intraoperatively in patients who underwent KA through a systematic review and meta-analysis. Methods A systematic search was conducted to identify relevant randomized controlled trials in the PubMed, Embase, Web of Science and Cochrane databases up to January 19th, 2021 to perform a meta-analysis. Outcome variables included pain scores, total opioid consumption, knee range of motion (ROM) and postoperative complications. Results Corticosteroid injections did not reduce pain scores at 6, 12, 24 or 72 h postoperatively, although a minimal degree of transient pain relief was achieved at 48 h postoperatively compared with those in the placebo group, nor was there a significant difference in total opioid consumption. However, patients receiving corticosteroids did exhibit a transient ROM increase on postoperative days 1, 2 and 3. Since the minimal clinically important difference (MCID) for ROM is unclear, it is unknown if the improvement in ROM is clinically significant. What is new and conclusion Our specific end-point analysis demonstrated that corticosteroid administration did not provide pain relief or reduce opioid consumption compared with placebo. However, corticosteroids might provide a statistically significant, though transient and minimal improvement in knee ROM after KA, although no firm conclusions about the benefits of administering corticosteroids in KA can be made based on the available evidence.

Summary Positive nucleic acid (NA) results have been found in recovered and discharged COVID-19 patients, but the proportion is unclear. This study was designed to analyze the recurrent positive rate of NA results after consecutively negative results, and the relationship between the specific antibody production and positive NA rate. According to Strengthening the Reporting of Observational Studies in Epidemiology guidelines, data of inpatients in Sino-French New City Branch of Tongji Hospital between Jan. 28 and Mar. 6, 2020 were collected. A total of 564 COVID-19 patients over 14 years old who received the examinations of NA and antibodies against SARS-CoV-2 were included. Days of viral shedding and specific antibodies were recorded and assessed. Among NA tests in respiratory samples (throat swabs, nasopharyngeal swabs, sputum and flushing fluid in alveoli), the patients with all-negative NA results accounted for 17.20%, those with single-positive results for 46.63%, and those with multiple-positive results for 36.17% respectively. Besides, the recurrent positive NA results after consecutively negative results appeared in 66 patients (11.70%). For multiple-positive patients, median viral shedding duration was 20 days (range: 1 to 57 days). Of the 205 patients who received 2 or more antibody tests, 141 (68.78%) had decreased IgG and IgM concentrations. IgM decreased to normal range in 24 patients, with a median of 44 days from symptom onset. Viral shedding duration was not significantly correlated with gender, age, disease severity, changes in pulmonary imaging, and antibody concentration. It is concluded that antibody level and antibody change had no significant correlation with the positive rate of NA tests and the conversion rate after continuous negative NA tests. In order to reduce the recurrent positive proportion after discharge, 3 or more consecutive negative NA test results with test interval more than 24 h every time are suggested for the discharge or release from quarantine.

Competition among academic institutions for students and Industry 4.0 have spurred institutions to actively improve undergraduates’ learning experiences and outcomes. The objectives of this research are to identify the quality dimensions of maritime studies programmes from students’ perspectives and examine their impacts on learning outcomes which include satisfaction, engagement, and academic performance. After reviewing the literature, six quality dimensions containing 29 measurement items were generated. An online survey was conducted on maritime students from Nanyang Technological University, Singapore. Thereafter, exploratory factor analysis and path analysis were used to analyse the survey data. The exploratory factor analysis produces a six-factor solution that confirms the proposed quality dimensions. Further, the quality dimension with the most impact on student satisfaction is (1) technology integration, followed by (2) industrial exposure, (3) learning and teaching environment, (4) industry-aligned & innovative curriculum, (5) faculty member competencies, and finally (6) supporting activities. In addition, student satisfaction positively influences engagement and academic performance. Further, engagement positively influences academic performance. The developed quality dimension model can serve as a measurement tool for maritime institutions to assess the quality of their programme and update their curriculums respectively to meet students’ expectations and learning outcomes.

Optical fiber cascaded Fabry–Perot interferometers temperature sensors based on Vernier effect are studied in detail by theoretical simulation. The simulation results show that the free spectrum range (FSR) difference of the two Fabry–Perot interferometers affects the temperature sensitivity. When the value of the FSR difference is positive, the temperature sensitivity is positive too. Otherwise, the temperature sensitivity is negative. Furthermore, the temperature sensitivity of the Fabry–Perot interferometer sensors based on Vernier effect is higher with the FSR difference smaller. Therefore, we propose a method for controlling the sensitivity of the Fabry–Perot interferometer sensors based on Vernier effect by adjusting the difference of the two FSR.

Perimenopausal syndrome (PMS) has a high incidence rate and affects the physical and mental health of middle-aged and elderly women. The blockage of PMS is significant in improving the health of perimenopausal women. Currently, for PMS prevention and treatment, traditional Chinese medicine (TCM) has become an ideal choice because of its safety and effectiveness. This study aimed to explore the anti-PMS effects of Ziyin Bushen Decoction (DKTP) and the underlying mechanism. Thirty female Wistar rats were divided into 5 groups (n = 6): control group, low-dose DKTP group, medium-dose DKTP group, high-dose DKTP group, and nilestriol group. The estradiol (E2) level in rat peripheral blood was analyzed using an E2 Radioimmunoassay Kit, and uterine morphologic changes were examined by hematoxylin-eosin staining. Learning and memory ability of rats was assessed by Morris water maze (MWM) and novel object recognition (NOR) task. E2 synthesis, metabolism, and transport associated estrogen receptor-alpha (ERα), GnRHR, CYP17, CYP11A1, CYP19, 17βHSD, STS, and SHGB were assessed to explore the E2-promoting mechanism of DKTP during PMS treatment. The loss of learning and memory, the decreased estrous and uterine coefficient, and the presence of histopathological changes suggests a successful establishment of rat PMS model. Following DKTP or nilestriol treatment, the above results were reversed. E2 level in serum, uterine, and ovarian tissues was upregulated upon different concentrations of DKTP treatment, indicating that DKTP promotes the E2 level in a dose-dependent manner. DKTP also increased the expression of ERα, CYP17, CYP11A1, CYP19, 17βHSD, STS, and SHGB while decreased the GnRHR expression in uterine and ovarian tissues, revealing that these key molecules involved in estrogen synthesis, metabolism, and transport in PMS rats. We confirmed the anti-PMS effect of DKTP through enhancing E2 production. Exploring a novel drug based on improving E2 synthesis, metabolism, and transport may represent a novel strategy for PMS prevention and treatment.

Bone defects or fractures generally heal in the absence of major interventions due to the high regenerative capacity of bone tissue. However, in situations of severe/large bone defects, these orchestrated regeneration mechanisms are impaired. With advances in modern medicine, natural and synthetic bio-scaffolds from bioceramics and polymers that support bone growth have emerged and gained intense research interest. In particular, scaffolds that recapitulate the molecular cues of extracellular signals, particularly growth factors, offer potential as therapeutic bone biomaterials. The current challenges for these therapies include the ability to engineer materials that mimic the biological and mechanical properties of the real bone tissue matrix, whilst simultaneously supporting bone vascularization. In this review, we discuss the very recent innovative strategies in bone biomaterial technology, including those of endogenous biomaterials and cell/drug delivery systems that promote bone regeneration. We present our understanding of their current value and efficacy, and the future perspectives for bone regenerative medicine.

This paper investigates controllability of a class of hybrid systems modeled by a hybrid machine consisting of an automaton for discrete events and a dynamic system for continuous variables. Control of discrete events is achieved by forcing some forcible events and disabling some controllable events. Depending on which events are forcible and/or controllable and on the connectivity of the automaton, the hybrid system may or may not be controllable. For the case that all events are controllable and forcible and the automaton is strongly connected, a necessary and sufficient condition for controllability is obtained, using some existing results on controllability of switched linear systems. For three other cases, sufficient conditions are derived. An example of an autonomous electric vehicle is given to illustrate the results.

Gastric cancer(GC) remains the fourth-leading malignancy worldwide and has a high mortality rate.Accumulating evidence reveals that long noncoding RNAs (lncRNAs) play essential roles in tumorigenesis and metastasis and can be used as potential biomarkers for diagnosis and prognosis. The current study sought to define the lncRNA LUCAT1 and verify its malignant biological behaviors in GC. We conducted bioinformatic analysis to screen differentially expressed lncRNAs between GC tissue and paracancerous tissue. Gene expression profiles were downloaded from the National Center of Biotechnology Information Gene Expression Omnibus(GEO). Real-time quantitative polymerase chain reaction (RT-qPCR) was carried out to verify LUCAT1 expression in both GC tissue and paracancerous tissue. Furthermore, the associations between LUCAT1 and clinical features were analyzed. In addition, the malignant behaviors of LUCAT1 in GC were investigated by knocking down LUCAT1 expression in the SGC7901 and AGS cell lines. The results indicated that LUCAT1 expression was obviously upregulated in GC samples compared with paracancerous tissue samples. Moreover, the expression pattern of LUCAT1 showed close correlations with tumor diameter (P

Background: TBK1 haploinsufficiency has been shown to cause both amyotrophic lateral sclerosis (ALS) and frontotemporal dementia (FTD); however, the mechanism is unclear. Methods: A myeloid Tbk1 knockout mice (Tbk1-LKO mice) was established. Motor functional and pathological analyses were also performed. The p-TBK1 was tested by flow cytometry in the ALS animal model and patients. The inflammatory proteins and mRNA was analyzed by Western blot and RT-PCR.Results: We found that the latency to fall in seven-month-old Tbk1-LKO mice was significantly reduced on evaluation on two consecutive days. Overall, 25.6% of Tbk1-LKO mice presented paralysis symptoms and signs along with a loosened myelin sheath and axon degeneration at 14-16 months of age. Furthermore, Tbk1 deficiency in myeloid cells induced inflammatory cell infiltration and dysbacteriosis in the digestive tract. Additionally, p-Tbk1 content was reduced by 29.5% and 14.8% in monocytes of definite ALS and probable ALS patients and decreased by 27.6% and 45.5% in the monocytes and microglia of ALS animals, respectively. PEI-mannose-TBK1 or PEI-mannose-SaCas9-sgRNA for deleting mutant SOD1 in macrophages significantly delayed disease onset and prolonged survival in the ALS mouse model. Conclusions: These data suggest that inflammatory monocyte and macrophage infiltration and impaired innate immune defense are contributing factors to ALS and FTD.

Background Cases of Wallerian degeneration of bilateral cerebral peduncles after acute carbon monoxide poisoning have not yet been reported. To date, most of the delayed encephalopathy after acute carbon monoxide poisoning (DEACMP) lesions captured in magnetic resonance imaging (MRI) has been located in the subcortical white matter and basal ganglia. Here we report two cases of DEACMP with abnormalities in the bilateral cerebral peduncles. The etiology of abnormalities, which were strictly confined to the bilateral cerebral peduncles, was Wallerian degeneration secondary to upstream nerve axonal damage, making this the first report on such bilateral cerebral peduncle abnormalities after DEACMP. Case presentation In this report, we present two cases of DEACMP with abnormal signals in the bilateral cerebral peduncles captured during brain MRIs. Case 1 was of a 68-year-old man who presented with paroxysmal disturbance of the consciousness, left limb weakness for 16 days, and lagging responses for 2 days. Case 2 was of a 55-year-old man who was unconscious for 6 h. In addition to the above mentioned characteristics on the brain MRIs, the electroencephalography of case 1 indicated that his forehead scans had a mixture of wide sharp, sharp, and three-phase waves. Brain diffusion tensor imaging of case 2 further proved that the bilateral cerebral anomalies represented Wallerian degeneration secondary to upstream axonal damage. After the definitive diagnosis, the patients returned to the local hospital for hyperbaric oxygen therapy. Conclusions Wallerian degeneration of the bilateral cerebral peduncles after acute carbon monoxide poisoning has never been reported before. The abnormal signals in the bilateral cerebral peduncles captured during brain MRIs indicated Wallerian degeneration secondary to upstream axonal damage; thus, these two cases may further our understanding of DEACMP imaging.

Traditional Chinese Medicine (TCM) is one of the ancient and most accepted alternative medicinal systems in the world for the treatment of health ailments. World Health Organization recognizes TCM as one of the primary healthcare practices followed across the globe. TCM utilizes a holistic approach for the diagnosis and treatment of cancers. The tumor microenvironment (TME) surrounds cancer cells and plays pivotal roles in tumor development, growth, progression, and therapy resistance. TME is a hypoxic and acidic environment that includes immune cells, pericytes, fibroblasts, endothelial cells, various cytokines, growth factors, and extracellular matrix components. Targeting TME using targeted drug delivery and nanoparticles is an attractive strategy for the treatment of solid tumors and recently has received significant research attention under precise medicine concept. TME plays a pivotal role in the overall survival and metastasis of a tumor by stimulating cell proliferation, preventing the tumor clearance by the immune cells, enhancing the oncogenic potential of the cancer cells, and promoting tumor invasion. Hepatocellular Carcinoma (HCC) is one of the major causes of cancer-associated deaths affecting millions of individuals worldwide each year. TCM herbs contain several bioactive phytoconstituents with a broad range of biological, physiological, and immunological effects on the system. Several TCM herbs and their monomers have shown inhibitory effects in HCC by controlling the TME. This study reviews the fundamentals and applications of targeting strategies for immunosuppressing TME to treat cancers. This study focuses on TME targeting strategies using TCM herbs and the molecular mechanisms of several TCM herbs and their monomers on controlling TME.

The mission-critical nature of wireless networked sensing and control (WSC) systems, such as the control of industrial plants, requires stringent real-time delivery of packets. Due to inherent dynamics and uncertainties in wireless communication, real-time communication guarantees are probabilistic in nature. In this paper, a probabilistic framework is therefore proposed for per-packet real-time delivery guarantee. The notion of real-time in this paper differs from the existing work in the sense that it ensures, in an execution history of arbitrary length, every packet is successfully delivered before its deadline with a probability no less than a user-specified threshold (e.g., 99%). The framework has several novel building blocks: First, “R3 (requirement-reliability-resource) mapping” translates the upper layer probabilistic real-time communication requirement , and the lower layer links reliability into the resource (i.e., optimal number of transmission opportunities) reserved for each packet. Second, “EDF (earliest deadline first) based real-time scheduling” as well as the “admission test” and “traffic load optimization” maximize system utility while satisfying per-packet real-time communication requirements. The proposed admission test is proved to be both sufficient and necessary, and the simulation results show that the proposed framework ensures probabilistic per-packet real-time communication.

This paper investigates optimal power management in dc microgrids, with its applications to dc dual-source trolleybus systems. High mobility of buses and their impact on power supply networks introduce challenging power management issues. This paper incorporates line power losses in power management strategies and introduces a new distributed optimal power management methodology. A multi-objective optimization model is developed. Using only neighborhood information exchange among feeder lines in the network, the new consensus-type control accommodates both feeder current allocation and power loss reduction with fast convergence. One critical finding of this paper is that our local recursive optimization algorithms achieve the global optimal solution asymptotically. Under random noise on information exchange, convergence and optimality of the proposed method are established rigorously. The power system configurations of the Beijing dual-source trolleybus system are used for simulation case studies on the new power management methods. Feasibility, accuracy, and comparison with global optimization results are demonstrated.

Distributed generators, controllable appliances, electric vehicle charging infrastructures, and energy storage systems introduce new technical challenges to the management of distribution networks, especially when there are large power fluctuations. Interactive dynamics between load and distributed generators in a distribution network carry significant impact on voltage variation and transient during load power disturbances. It is shown in this paper that the traditional static power flow analysis, in which load dynamic behavior is not counted, is not sufficient to model and predict voltage excursion after a power disturbance. To capture the behavior of load types and dynamics, this paper employs Hammerstein model structures to represent such behavior and explore their real-time identification. This is especially important for voltage quality management since the load dynamics depend on active and reactive load power, and hence change substantially due to load/generator power perturbations, electric vehicle charging activities, and subsystem load type varieties. Identification algorithms are introduced and their convergence properties are established. The algorithms are applied to a generic grid structure first, then evaluated on a 33-Bus system with multiple dynamic loads.

Connected and automated vehicles mandate integrated design of communications and control to achieve coordination of highway vehicles. Random features of wireless communications introduce new types of uncertainties into networked systems and impact control performance significantly. Due to typical packet loss, erasure channels create random link interruption and switching in network topologies. This paper models such switching network topologies by Markov chains and derives their probability transition matrices from stochastic characterizations of the channels. Impact of communication erasure channels on vehicle platoon formation and robustness under a weighted and constrained consensus framework is analyzed. By comparing convergence properties of networked control algorithms under different communication channel features, we characterize some intrinsic relationships between packet delivery ratio and convergence rate. Simulation case studies are performed to verify the theoretical findings.

The open circuit voltage (OCV) is an essential variable for accurate state of charge (SoC) estimation of lithium ion batteries in electric vehicles (EVs). OCV test must be performed periodically to calibrate the OCV-SoC relationship after battery aging. Furthermore, due to pronounced hysteresis effects and wide flat regions in the OCV-SoC curves of LiFePO4 batteries, the traditional OCV tests often take three to five days to obtain data on one or more fully charge and discharge cycles, which are time-consuming and become unreliable under changing driving cycles and operating conditions. In addition, the OCV-SoC relationship determined in a certain aging stage cannot be used for the full life cycle and whole operating conditions. In this paper, the OCV-SoC relationship is extracted from any existing current-voltage measurements by using an H infinity filter within several seconds, which is verified under constant current conditions and dynamic conditions. Our results show that the estimated OCV can result in accurate SoC estimation with a maximum error of 1%.

Although hand hygiene (HH) is the most effective intervention to reduce the spread of infections, there are limited data on HH facilities, policy, and compliance in sub-Saharan Africa. This cross-sectional study is aimed at assessing HH using the WHO HH self-assessment framework, HH technical reference manual, and a modified infection control self-assessment tool in two hospitals in Sierra Leone. Only 10% and 9% of regional and capital city hospitals had running tap water, respectively. Veronica buckets were the resources for HH in 89% of units in the regional hospital and 92% of units in capital city hospital. Constant supply of soap and alcohol-based hand rub was available in 82% and 68%; and 74% and 79% of units in the capital city and regional hospitals, respectively. Only 10% of the units in both hospitals had hand-drying facilities and functional sinks. Overall HH compliance for the two hospitals was 18.6% and was higher in the regional (20.8%) than the capital city (17.0%) hospitals. The HH levels for the capital city and regional hospitals were 277.5 and 262.5 respectively. Despite the COVID-19 pandemic, there are still challenges with HH compliance in Sierra Leone. It is, therefore, necessary to strengthen the HH multi-modal strategy.

This paper analyzes the reliability of large scale battery storage systems consisting of multiple battery modules. The whole system reliability assessment is based on the reliability evaluation of system components including individual battery modules and power electronic converters. In order to evaluate the reliability of a battery module, a reliability model based on the state of health of individual battery cells is introduced. The state of health of a battery cell is calculated based on the capacity fade of the cell using a weighted Ampere-hour throughput method. A universal generating function-based method is then introduced to evaluate the reliability of the battery module. The reliability model of dc/ac power electronic converters is also presented in this paper. The reliability analysis is conducted for battery storage systems with different system configurations and management strategies, and the influence of system configuration on the reliability of battery system is studied. Comparative studies are conducted for a classic battery energy storage system (BESS) and a reconfigurable BESS (RBESS) to demonstrate the advantages of having a reconfigurable system topology. The comparison results show that the proposed RBESS has higher system reliability and more power outputs than the classic BESS.

In this paper, we investigate active on-line diagnosis in discrete event systems. Active diagnosis can be used for fault detection, fault localization, fault-tolerant control, among others. Discrete event systems are general models for complex manmade systems. For the active on-line diagnosis, we do not construct the entire diagnostic automaton off-line. Instead, we look N steps ahead to determine active diagnosability and calculate diagnostic strategies. Thus, we define active N -diagnosability and investigate the relation between active diagnosability and active N -diagnosability. We also develop an algorithm to check active N -diagnosability. If a system is actively N -diagnosable, the algorithm will also give the control that diagnoses the system. We show that there are significant computational advantages for using the on-line approach.

This paper analyzes system-level capacity, stored energy, and power loss, and introduces methods for their diagnosis with reliability characterization, for networked battery systems. Since system-level features of a networked battery system are functions of its member battery packs, it is of essential importance to establish rigorously this component-to-system relationship. The paper provides a method to calculate accurately diagnosis error probabilities on the system-level quantities when individual batteries’ measurements are subject to measurement errors and their characterizing parameters are estimated from such measurements. These results are then used to choose diagnosis decision variables such as the thresholds for detecting faulty batteries and data sizes for estimation. Focusing on stored energy, capacity, and power loss, this paper characterizes error statistics of estimation algorithms for these quantities. Convergence of the algorithms, asymptotic probability distributions of the estimates, and diagnosis reliability analysis are performed rigorously by using stochastic differential equations, central limit theorems, and large deviations principles. Simulated case studies and experimental data are used to illustrate the methods and their usefulness.

Dual-source electric vehicles powered by both on-board battery and grid electricity offer unique advantages in fuel economy, cost reduction, driveability, and grid support, which are especially appealing for public transportation in populated cities. The structures of their power supply systems create naturally a networked system of vehicles sharing common feeders. Their power management and control strategies must individually enhance each vehicle’s local performance, and coordinate globally to limit the grid peak current, reduce current fluctuations, and improve efficiency. This paper introduces a novel methodology that employs load prediction, optimal control, and distributed predictive control for current management in such networked systems without vehicle-to-vehicle communications. Estimation and control strategies are introduced, and computationally efficient recursive algorithms are developed. The power system configuration of the Beijing dual-source trolleybus system is used for simulation case studies on the new management strategies. Estimation accuracy, prediction reliability, and performance improvement from the integrated predictive control strategies are demonstrated. Successful implementation of the methodology can potentially attenuate feeder current fluctuations, reduce feeder peak loads, and alleviate disturbances to main grids.

Large-scale and complex stochastic networked systems are common in broad spectra of applications, such as smart grids, finance, social networks, edge/cloud computing, etc. Many of such systems inevitably involve mean-field interactions. It is of essential importance to develop the methods for solving the optimal control problems. In this paper, we first present a number of motivational models and problems. Then we present new approaches for obtaining the maximum principle to treat large-scale switched systems with mean-field interactions. One of the key ideas is to use the conditional mean field. The maximum principle forms a foundation on which we can solve the corresponding LQG (linear quadratic Gaussian) regulation problems. We also consider the case that the modulating Markov chain switches rapidly with weak and strong interactions. In such a case, the discrete part of the state space becomes nearly decomposable. We show the optimal controls can be obtained.

Background Available data on antibiotic resistance in sub-Saharan Africa is limited despite its increasing threat to global public health. As there is no previous study on antibiotic resistance in patients with clinical features of healthcare-associated infections (HAIs) in Sierra Leone, research is needed to inform public health policies. Our study aimed to assess antibiotic resistance rates from isolates in the urine and sputum samples of patients with clinical features of HAIs. Methodology We conducted a cross-sectional study of adult inpatients aged ≥18 years at Connaught Hospital, an urban tertiary care hospital in Freetown between February and June 2018. Results Over the course of the study, we enrolled 164 patients. Risk factors for HAIs were previous antibiotic use (93.3%), comorbidities (58.5%) and age (≥65 years) (23.9%). Of the 164 samples, 89.6% were urine. Bacterial growth was recorded in 58.8% of cultured specimens; the type of specimen was an independent predictor of bacterial growth (p Escherichia coli and Klebsiella pneumoniae; 29.2% and 19.0% in urine samples and 18.8% and 31.3% in sputum samples, respectively. The overall resistance rates were 58% for all extended-spectrum beta-lactamase (ESBL)-producing organisms, 13.4% for carbapenem-resistant non-lactose fermenting gram-negative bacilli, 8.7% for carbapenem-resistant Acinetobacter baumannii (CRAB) and 1.3% for carbapenem-resistant Enterobacteriaceae (CRE). There were no carbapenem-resistant P. aeruginosa (CRPA) isolates but all Staphylococcus aureus isolates were methicillin-resistant S. aureus. Conclusion We demonstrated a high prevalence rate of ESBL-producing organisms which are a significant burden at the main tertiary hospital in Sierra Leone. Urgent action is needed to strengthen microbiological diagnostic infrastructure, initiate surveillance on antibiotic resistance and develop and implement policy framework on antibiotic stewardship.

The environmental sustainability stimulates the development of electric vehicles with great energy-saving and emission reduction effects. State of health of the battery system in an electric vehicle is crucial to the safety of vehicle operation, charging station, and the environment. The existing techniques implemented in well-controlled experimental environments fail to learn unpredictable drivers’ driving behaviors and complex road/weather conditions during actual vehicular operation. This paper investigates a novel deep-learning-enabled method to perform accurate state of health estimation for battery systems on real-world electric vehicles. Eight potential evaluation schemes depending on the stable charging stages are recapped and discussed. By fitting the correlation between battery degeneration factors and various vehicle operation parameters such as ambient temperature and mileage, an approximate battery degeneration model oriented for the real application scenarios is obtained. The variable-length-input long short-term memory network is used to learn the variable battery degeneration factors acquired from different driving stages of a yearlong dataset. The test results show that the proposed method has a better performance than other estimation methods. More significantly, based on the acquisition advantages of big-data platforms, it can be used to full-state and full-climate vehicle applications unrestricted by complex actual environments.

Many environmental stressors, including stress temperature, high density, hypoxia, low food availability, high social pressure, and bright background colour, have been found to cause masculinization in fish. The environmental-friendly factors-induced masculinization provides a possibility of environmental-friendly mono-sex production for aquaculture. In the present work, we found high temperature (33.5 °C) or cortisol administration (300 mg kg−1 feed) covering the critical period of ovarian differentiation (15–38 days post-fertilization, DPF) caused partial masculinization of XX genotype in yellow catfish, via the application of sex-linked markers and successive histological analysis containing critical time window of ovarian and testicular differentiation and differentiated gonads, including 25 DPF, 35 DPF, 45 DPF, 65 DPF, and 125 DPH of XX female, XX male, and XY male. The masculinization modes in high temperature and cortisol administration groups were similar, including repression of primordial germ cells proliferation and retention of the ovarian cavity in XX pseudo-male. XX male was similar to XY male at both transcriptional and morphological levels, via RNA-seq analysis and morphological characteristics and gonadal histology respectively, providing a possibility to produce functional XX males and all-female XX population on a large-scale through an environmental-friendly approach for yellow catfish. The establishment and application of an environmental-friendly approach for mono-sex production will reduce the usage of steroid hormones and functionally similar chemicals in the aquaculture industry.

The platooning of autonomous vehicles has the potential to significantly improve traffic capacity, enhance highway safety, and reduce fuel consumption. This paper studies the scalability limitations of large-scale vehicular platoons moving in rigid formation, and proposes two basic ways to improve stability margins, i.e., enlarging information topology and employing asymmetric control. A vehicular platoon is considered as a combination of four components: 1) node dynamics; 2) decentralized controller; 3) information flow topology; and 4) formation geometry. Tools, such as the algebraic graph theory and matrix factorization technique, are employed to model and analyze scalability limitations. The major findings include: 1) under linear identical decentralized controllers, the stability thresholds of control gains are explicitly established for platoons under undirected topologies. It is proved that the stability margins decay to zero as the platoon size increases unless there is a large number of following vehicles pinned to the leader and 2) the stability margins of vehicular platoons under bidirectional topologies using asymmetric controllers are always bounded away from zero and independent of the platoon size. Simulations with a platoon of passenger cars are used to demonstrate the findings.

Dual-source trolleybuses powered by onboard battery and grid electricity offer unique advantages in fuel economy, cost reduction, and passenger capacity, which are particularly appealing for public transportation in populated cities. Their mobility and power supply network configurations introduce challenging power management issues on their dedicated supply power grids. To ensure safe, reliable, and efficient operation of trolleybuses, their high-current and dynamic loads must be distributed to the feeders properly and promptly. Based on certain emerging networks of feeders and supply stations for city trolleybus systems, this paper introduces a new framework for current flow balancing based on recently developed weighted-and-constrained consensus control methods to manage the power supply network. Using only neighborhood information exchange among feeder lines in the network, the consensus control can achieve global current balancing with fast convergence to a balanced state, robustness to load perturbations, reconfiguration with feeder addition and deletion, and rebalancing under feeder capacity variation. The methodology is scalable in the sense that system expansion will not substantially increase the control system complexity. The power system configurations of the Beijing dual-source trolleybus system are used for simulation case studies on the new power management methods. Robustness and scalability are demonstrated, together with discussions on the feasibility, flexibility, and implementation issues of the methodology.

This paper develops new balanced charge/discharge strategies that distribute charge or discharge currents properly so that during operation, battery systems maintain uniform state-of-charge (SOC) all the time. The proposed balanced charge/discharge control strategies are useful for interconnected heterogeneous battery systems that can be built from battery modules with different types, ages, and power/capacity ratings. Both voltage-based and SOC-based balanced charge/discharge strategies are developed. Their convergence properties are rigorously established, and illustrative examples using production batteries demonstrate their convergence behavior under different charging current profiles. The approach will be especially useful for battery storage systems to support power grids with renewable energy sources where the battery systems are required to operate continuously.

Predictable inter-vehicle communication reliability is a basis for the paradigm shift from the traditional singlevehicle-oriented safety and efficiency control to networked vehicle control. The lack of predictable interference control in existing mechanisms of inter-vehicle communications, however, makes them incapable of ensuring predictable communication reliability. For predictable interference control, we propose the Cyber-Physical Scheduling (CPS) framework that leverages the PRK interference model and addresses the challenges of vehicle mobility to PRK-based scheduling. In particular, for lightweight control signaling and effective interference relation estimation, CPS leverages the physical locations of vehicles to define the gPRK interference model as a geometric approximation of the PRK model; for effective use of the gPRK model, CPS leverages cyber-physical structures of vehicle traffic flows, particularly, the spatiotemporal interference correlation as well as the macroand micro-scopic vehicle dynamics. Through experimental analysis with high-fidelity ns-3 and SUMO simulation, we observe that CPS enables predictable reliability while achieving high throughput and low delay in communication. To the best of our knowledge, CPS is the first field-deployable method that ensures predictable interference control and thus reliability in inter-vehicle communications.

Fast charging stations enable the high-powered rapid recharging of electric vehicles. However, these stations also face challenges due to power fluctuations, high peak loads, and low load factors, affecting the reliable and economic operation of charging stations and distribution networks. This paper introduces a battery energy storage system (BESS) for charging load control, which is a more user-friendly approach and is more robust to perturbations. With the goals of peak-shaving, total electricity cost reduction, and minimization of variation in the state-of-charge (SOC) range, a BESS-based bi-level optimization strategy for the charging load regulation of fast charging stations is proposed in this paper. At the first level, a day-ahead optimization strategy generates the optimal planned load curve and the deviation band to be used as a reference for ensuring multiple control objectives through linear programming, and even for avoiding control failure caused by insufficient BESS energy. Based on this day-ahead optimal plan, at a second level, real-time rolling optimization converts the control process to a multistage decision-making problem. The predictive control-based real-time rolling optimization strategy in the proposed model was used to achieve the above control objectives and maintain battery life. Finally, through a horizontal comparison of two control approaches in each case study, and a longitudinal comparison of the control robustness against different degrees of load disturbances in three cases, the results indicated that the proposed control strategy was able to significantly improve the charging load characteristics, even with large disturbances. Meanwhile, the proposed approach ensures the least amount of variation in the range of battery SOC and reduces the total electricity cost, which will be of a considerable benefit to station operators.

The reliable operation of battery management systems depends critically on the accurate estimation of the state of charge (SOC) and characterizing parameters of a battery system. SOC estimation employs models that must be robust against variations in battery cell electrochemical features, aging, and operating conditions. This paper reveals that commonly used SOC estimation schemes are fundamentally flawed in providing the robustness of SOC estimation against model uncertainties. Parameter estimation methodologies and adaptive SOC estimation design are introduced in this paper to enhance SOC estimation accuracy and robustness. By a scrutiny of the impact of parameter variations on SOC estimation accuracy, the SOC–open-circuit-voltage mapping is identified to be the most critical function that must be accurately established. Identification algorithms are introduced, and their convergence properties are established. The integration of the identification algorithms and SOC estimation schemes lead to an adaptive SOC estimation framework that is superior over the existing methods in providing much improved accuracy and robustness. Experimental studies are conducted to validate the algorithms.

Packet loss in block erasure channels creates a randomly switching networked system that impacts control performance significantly. This paper employs safety of highway vehicle platoons as a platform to study such an impact. By autonomous intervehicle coordination, a platoon can potentially enhance safety, improve highway utility, increase fuel economy, and reduce emission. By comparing different information structures that utilize radar distance sensors and wireless communication channels, we characterize some intrinsic relationships between communication resources and control performance. The findings of this paper provide useful guidelines in communication resource allocations and vehicle coordination in vehicle safety problems.

In this work, the influences of coal moisture control (CMC) and coal briquette technology on structure and reactivity of cokes were investigated by adding a certain proportion of briquette into raw coal with different moisture. The coking experiments were carried out in a tested coke-oven of 70 kg, and the properties of as-obtained coke were analyzed by X-ray diffraction (XRD), scanning electron microscope (SEM) and so on. The coke reactivity index (CRI), coke strength after reaction (CSR) and the optical texture of different cokes were also measured. The results indicated that the two technologies both can improve the structure of coke and reduce the reactivity of coke. The improved coke properties can be attributed to forming a more compact microcrystalline structure of coke to enhance its pore wall structure, its optical texture index (OTI) and its graphitization degree. Noticeably, the introduction of CMC technology in coal briquette process can produce the superposition effect to the great improvement of the coke properties. In addition, the results also indicated that the introduction of CMC technology in coal briquette process can reduce the sulfur content of coke due to the overflowed sulfur in the form of gas during the coking, and can almost be equivalent to substitute 10% briquette in coal briquette process in the improvement of the CRI and CSR from coke, implying the reduced amount of briquette to save coal resources.

State of charge (SOC) is one of the most important parameters in battery management system (BMS). There are numerous algorithms for SOC estimation, mostly of model-based observer/filter types such as Kalman filters, closed-loop observers, and robust observers. Modeling errors and measurement noises have critical impact on accuracy of SOC estimation in these algorithms. This paper is a comparative study of robustness of SOC estimation algorithms against modeling errors and measurement noises. By using a typical battery platform for vehicle applications with sensor noise and battery aging characterization, three popular and representative SOC estimation methods (extended Kalman filter, PI-controlled observer, andH∞observer) are compared on such robustness. The simulation and experimental results demonstrate that deterioration of SOC estimation accuracy under modeling errors resulted from aging and larger measurement noise, which is quantitatively characterized. The findings of this paper provide useful information on the following aspects: (1) how SOC estimation accuracy depends on modeling reliability and voltage measurement accuracy; (2) pros and cons of typical SOC estimators in their robustness and reliability; (3) guidelines for requirements on battery system identification and sensor selections.

A novel, fully decentralized strategy to coordinate charge operation of electric vehicles is proposed in this paper. Based on stochastic switching control of on-board chargers, this strategy ensures high-efficiency charging, reduces load variations to the grid during charging periods, achieves charge completion with high probability, and accomplishes approximate “valley-filling”. Further improvements on the core strategy, including individualized power management, adaptive strategies, and battery support systems, are introduced to further reduce power fluctuation variances and to guarantee charge completion. Stochastic analysis is performed to establish the main properties of the strategies and to quantitatively show the performance improvements. Compared with the existing decentralized charging strategies, the strategies proposed in this paper can be implemented without any information exchange between grid operators and electric vehicles (EVs), resulting in a communications cost reduction. Additionally, it is shown that by using stochastic charging rules, a grid-supporting battery system with a very small energy capacity can achieve substantial reduction of EV load fluctuations with high confidence. An extensive set of simulations and case studies with real-world data are used to demonstrate the benefits of the proposed strategies.