A generic domain pruning technique for GDL-based DCOP algorithms in cooperative multi-agent systems

Generalized Distributive Law (GDL) based message passing algorithms, such as Max-Sum and Bounded Max-Sum, are often used to solve distributed constraint optimization problems in cooperative multi-agent systems (MAS). However, scalability becomes a challenge when these algorithms have to deal with constraint functions with high arity or variables with a large domain size. In either case, the ensuing exponential growth of search space can make such algorithms computationally infeasible in practice. To address this issue, we develop a generic domain pruning technique that enables these algorithms to be effectively applied to larger and more complex problems. We theoretically prove that the pruned search space obtained by our approach does not affect the outcome of the algorithms. Moreover, our empirical evaluation illustrates a significant reduction of the search space, ranging from 33% to 81%, without affecting the solution quality of the algorithms, compared to the state-of-the-art

A Rare Case of a Gastro-Peritoneal Fistula Following Laparoscopic Sleeve Gastrectomy Successfully Treated with Endoscopic Stenting

Gastro-peritoneal fistula is a rare but serious complication of laparoscopic sleeve gastrectomy with significant morbidity and mortality. We present the case of a 42-year-old man who underwent laparoscopic sleeve gastrectomy for morbid obesity and presented later with a history of chronic epigastric pain and severe reflux. Upper gastrointestinal series showed the presence of a communicating fistula between the stomach and the left hemi-diaphragm and peri-splenic area

The Use of the S-Quattro Dynamic External Fixator for the Treatment of Intra-Articular Phalangeal Fractures: A Review of the Literature

Intra-articular phalangeal fractures are a common injury. If left untreated, these injuries can lead to poor functional outcome with severe dehabilitating consequences, especially in younger patients

May Measurement Month: results of 12 national blood pressure screening programmes between 2017 and 2019

The first May Measurement Month (MMM) campaign, a global blood pressure (BP) screening programme, began in 2017 as an initiative of the International Society of Hypertension.1 Two subsequent annual campaigns have also been completed in consecutive years2,3 and having had to defer activities due to the COVID-19 pandemic in 2020 the fourth campaign was run in 2021, the results of which are currently in press. Since its initiation in 2017, volunteers from more than 100 countries have participated. The aims of MMM have remained consistent from the start—to raise awareness of the importance of the measurement of BP at the individual and population level and to provide a temporary pragmatic solution to the shortfall in BP screening programmes in countries around the world

Effect of injection timing and injection duration of manifold injected fuels in reactivity controlled compression ignition engine operated with renewable fuels

In the current work, an effort is made to study the influence of injection timing (IT) and injection duration (ID) of manifold injected fuels (MIF) in the reactivity controlled compression ignition (RCCI) engine. Compressed natural gas (CNG) and compressed biogas (CBG) are used as the MIF along with diesel and blends of Thevetia Peruviana methyl ester (TPME) are used as the direct injected fuels (DIF). The ITs of the MIF that were studied includes 45°ATDC, 50°ATDC, and 55°ATDC. Also, present study includes impact of various IDs of the MIF such as 3, 6, and 9 ms on RCCI mode of combustion. The complete experimental work is conducted at 75% of rated power. The results show that among the different ITs studied, the D+CNG mixture exhibits higher brake thermal efficiency (BTE), about 29.32% is observed at 50° ATDC IT, which is about 1.77, 3.58, 5.56, 7.51, and 8.54% higher than D+CBG, B20+CNG, B20+CBG, B100+CNG, and B100+CBG fuel combinations. The highest BTE, about 30.25%, is found for the D+CNG fuel combination at 6 ms ID, which is about 1.69, 3.48, 5.32%, 7.24, and 9.16% higher as compared with the D+CBG, B20+CNG, B20+CBG, B100+CNG, and B100+CBG fuel combinations. At all ITs and IDs, higher emissions of nitric oxide (NOx) along with lower emissions of smoke, carbon monoxide (CO), and hydrocarbon (HC) are found for D+CNG mixture as related to other fuel mixtures. At all ITs and IDs, D+CNG gives higher In-cylinder pressure (ICP) and heat release rate (HRR) as compared with other fuel combinations

Detecting undiagnosed atrial fibrillation in UK primary care: Validation of a machine learning prediction algorithm in a retrospective cohort study

Aims To evaluate the ability of a machine learning algorithm to identify patients at high risk of atrial fibrillation in primary care. Methods A retrospective cohort study was undertaken using the DISCOVER registry to validate an algorithm developed using a Clinical Practice Research Datalink (CPRD) dataset. The validation dataset included primary care patients in London, England aged ≥30 years from 1 January 2006 to 31 December 2013, without a diagnosis of atrial fibrillation in the prior 5 years. Algorithm performance metrics were sensitivity, specificity, positive predictive value, negative predictive value (NPV) and number needed to screen (NNS). Subgroup analysis of patients aged ≥65 years was also performed. Results Of 2,542,732 patients in DISCOVER, the algorithm identified 604,135 patients suitable for risk assessment. Of these, 3.0% (17,880 patients) had a diagnosis of atrial fibrillation recorded before study end. The area under the curve of the receiver operating characteristic was 0.87, compared with 0.83 in algorithm development. The NNS was nine patients, matching the CPRD cohort. In patients aged ≥30 years, the algorithm correctly identified 99.1% of patients who did not have atrial fibrillation (NPV) and 75.0% of true atrial fibrillation cases (sensitivity). Among patients aged ≥65 years (n = 117,965), the NPV was 96.7% with 91.8% sensitivity. Conclusions This atrial fibrillation risk prediction algorithm, based on machine learning methods, identified patients at highest risk of atrial fibrillation. It performed comparably in a large, real-world population-based cohort and the developmental registry cohort. If implemented in primary care, the algorithm could be an effective tool for narrowing the population who would benefit from atrial fibrillation screening in the United Kingdom

The use of medicinal plants in health care practices by Rohingya refugees in a degraded forest and conservation area of Bangladesh

People in developing countries traditionally rely on plants for their primary healthcare. This dependence is relatively higher in forests in remote areas due to the lack of access to modern health facilities and easy availability of the plant products.We carried out an ethno-medicinal survey in Teknaf Game Reserve (TGR), a heavily degraded forest and conservation area in southern Bangladesh, to explore the diversity of plants used by Rohingya refugees for treating various ailments. The study also documented the traditional utilization, collection and perceptions of medicinal plants by the Rohingyas residing on the edges of this conservation area. We collected primary information through direct observation and by interviewing older respondents using a semi-structured questionnaire. A total of 34 plant species in 28 families were frequently used by the Rohingyas to treat 45 ailments, ranging from simple headaches to highly complex eye and heart diseases. For medicinal preparations and treating various ailments, aboveground plant parts were used more than belowground parts. The collection of medicinal plants was mostly from the TGR. © 2009 Taylor & Francis

Genetic risk factors for ischaemic stroke and its subtypes (the METASTROKE Collaboration): a meta-analysis of genome-wide association studies

<p>Background - Various genome-wide association studies (GWAS) have been done in ischaemic stroke, identifying a few loci associated with the disease, but sample sizes have been 3500 cases or less. We established the METASTROKE collaboration with the aim of validating associations from previous GWAS and identifying novel genetic associations through meta-analysis of GWAS datasets for ischaemic stroke and its subtypes.</p> <p>Methods - We meta-analysed data from 15 ischaemic stroke cohorts with a total of 12 389 individuals with ischaemic stroke and 62 004 controls, all of European ancestry. For the associations reaching genome-wide significance in METASTROKE, we did a further analysis, conditioning on the lead single nucleotide polymorphism in every associated region. Replication of novel suggestive signals was done in 13 347 cases and 29 083 controls.</p> <p>Findings - We verified previous associations for cardioembolic stroke near PITX2 (p=2·8×10−16) and ZFHX3 (p=2·28×10−8), and for large-vessel stroke at a 9p21 locus (p=3·32×10−5) and HDAC9 (p=2·03×10−12). Additionally, we verified that all associations were subtype specific. Conditional analysis in the three regions for which the associations reached genome-wide significance (PITX2, ZFHX3, and HDAC9) indicated that all the signal in each region could be attributed to one risk haplotype. We also identified 12 potentially novel loci at p<5×10−6. However, we were unable to replicate any of these novel associations in the replication cohort.</p> <p>Interpretation - Our results show that, although genetic variants can be detected in patients with ischaemic stroke when compared with controls, all associations we were able to confirm are specific to a stroke subtype. This finding has two implications. First, to maximise success of genetic studies in ischaemic stroke, detailed stroke subtyping is required. Second, different genetic pathophysiological mechanisms seem to be associated with different stroke subtypes.</p&gt

Phenytoin versus Leviteracetam for seizure prophylaxis after brain injury - A meta analysis

Background: Current standard therapy for seizure prophylaxis in Neuro-surgical patients involves the use of Phenytoin (PHY). However, a new drug Levetiracetam (LEV) is emerging as an alternate treatment choice. We aimed to conduct a meta-analysis to compare these two drugs in patients with brain injury.Methods: An electronic search was performed in using Pubmed, Embase, and CENTRAL. We included studies that compared the use of LEV vs. PHY for seizure prophylaxis for brain injured patients (Traumatic brain injury, intracranial hemorrhage, intracranial neoplasms, and craniotomy). Data of all eligible studies was extracted on to a standardized abstraction sheet. Data about baseline population characteristics, type of intervention, study design and outcome was extracted. Our primary outcome was seizures.Results: The literature search identified 2489 unduplicated papers. Of these 2456 papers were excluded by reading the abstracts and titles. Another 25 papers were excluded after reading their complete text. We selected 8 papers which comprised of 2 RCTs and 6 observational studies. The pooled estimate\u27s Odds Ratio 1.12 (95% CI = 0.34, 3.64) demonstrated no superiority of either drug at preventing the occurrence of early seizures. In a subset analysis of studies in which follow up for seizures lasted either 3 or 7 days, the effect estimate remained insignificant with an odds ratio of 0.96 (95% CI = 0.34, 2.76). Similarly, 2 trials reporting seizure incidence at 6 months also had insignificant pooled results while comparing drug efficacy. The pooled odds ratio was 0.96 (95% CI = 0.24, 3.79).Conclusions: Levetiracetam and Phenytoin demonstrate equal efficacy in seizure prevention after brain injury. However, very few randomized controlled trials (RCTs) on the subject were found. Further evidence through a high quality RCT is highly recommended