A Portfolio Selection Method Based on Pattern Matching with Dual Information of Direction and Distance

Pattern matching method is one of the classic classifications of existing online portfolio selection strategies. This article aims to study the key aspects of this method—measurement of similarity and selection of similarity sets, and proposes a Portfolio Selection Method based on Pattern Matching with Dual Information of Direction and Distance (PMDI). By studying different combination methods of indicators such as Euclidean distance, Chebyshev distance, and correlation coefficient, important information such as direction and distance in stock historical price information is extracted, thereby filtering out the similarity set required for pattern matching based investment portfolio selection algorithms. A large number of experiments conducted on two datasets of real stock markets have shown that PMDI outperforms other algorithms in balancing income and risk. Therefore, it is suitable for the financial environment in the real world.

Exact Graph Pattern Matching:Applications,Progress and Prospects

Graph pattern matching(GPM)can be used to mine the key information in graphs.Exact GPM is one of the most commonly used methods among all the GPM-related methods,which aims to exactly find all subgraphs for a given query graph in a data graph.The exact GPM has been widely used in biological data analyses,social network analyses and other fields.In this paper,the applications of the exact GPM were first introduced,and the research progress of the exact GPM was summarized.Then,the related algorithms were introduced in detail,and the experiments on the state-of-the-art exact GPM algorithms were conducted to compare their performance.Based on the experimental results,the applicable scenarios of the algorithms were pointed out.New research opportunities in this area were proposed.

Corrigendum to“Migration pattern of a population of Barn Swallows(Hirundo rustica)breeding in East Asian tropical region”[Avian Res.15(2024)100192]

The authors regret that the caption of Fig.4 should be replaced as below.

Understanding the Relationship Between Shrinking Cities and Land Prices:Spatial Pattern,Effectiveness,and Policy Implications

Urban shrinkage has emerged as a widespread phenomenon globally and has a significant impact on land,particularly in terms of land use and price.This study focuses on 2851 county-level cities in China in 2005–2018(excluding Hong Kong,Macao,Taiwan,and‘no data’areas in Qinhai-Tibet Plateau)as the fundamental units of analysis.By employing nighttime light(NTL)data to identify shrinking cities,the propensity score matching(PSM)model was used to quantitatively examine the impact of shrinking cities on land prices,and evaluate the magnitude of this influence.The findings demonstrate the following:1)there were 613 shrinking cities in China,with moderate shrinkage being the most prevalent and severe shrinkage being the least.2)Regional disparities are evident in the spatial distribution of shrinking cities,especially in areas with diverse terrain.3)The spatial pattern of land price exhibits a significant correlated to the economic and administrative levels.4)Shrinking cities significantly negatively impact on the overall land price(ATT=–0.1241,P<0.05).However,the extent of the effect varies significantly among different spatial regions.This study contributes novel insights into the investigation of land prices and shrinking cities,ultimately serving as a foundation for government efforts to promote the sustainable development of urban areas.

Clinical manifestation,lifestyle,and treatment patterns of chronic erosive gastritis:A multicenter real-world study in China

BACKGROUND Although chronic erosive gastritis(CEG)is common,its clinical characteristics have not been fully elucidated.The lack of consensus regarding its treatment has resulted in varied treatment regimens.AIM To explore the clinical characteristics,treatment patterns,and short-term outcomes in CEG patients in China.METHODS We recruited patients with chronic non-atrophic or mild-to-moderate atrophic gastritis with erosion based on endoscopy and pathology.Patients and treating physicians completed a questionnaire regarding history,endoscopic findings,and treatment plans as well as a follow-up questionnaire to investigate changes in symptoms after 4 wk of treatment.RESULTS Three thousand five hundred sixty-three patients from 42 centers across 24 cities in China were included.Epigastric pain(68.0%),abdominal distension(62.6%),and postprandial fullness(47.5%)were the most common presenting symptoms.Gastritis was classified as chronic non-atrophic in 69.9%of patients.Among those with erosive lesions,72.1%of patients had lesions in the antrum,51.0%had multiple lesions,and 67.3%had superficial flat lesions.In patients with epigastric pain,the combination of a mucosal protective agent(MPA)and proton pump inhibitor was more effective.For those with postprandial fullness,acid regurgitation,early satiety,or nausea,a MPA appeared more promising.CONCLUSION CEG is a multifactorial disease which is common in Asian patients and has non-specific symptoms.Gastroscopy may play a major role in its detection and diagnosis.Treatment should be individualized based on symptom profile.

Venous Doppler flow patterns,venous congestion,heart disease and renal dysfunction:A complex liaison

The World Journal of Cardiology published an article written by Kuwahara et al that we take the pleasure to comment on.We focused our attention on venous congestion.In intensive care settings,it is now widely accepted that venous congestion is an important clinical feature worthy of investigation.Evaluating venous Doppler profile abnormalities at multiple sites could suggest adequate treatment and monitor its efficacy.Renal dysfunction could trigger or worsen fluid overload in heart disease,and cardio-renal syndrome is a well-characterized spectrum of disorders describing the complex interactions between heart and kidney diseases.Fluid overload and venous congestion,including renal venous hypertension,are major determinants of acute and chronic renal dysfunction arising in heart disease.Organ congestion from venous hypertension could be involved in the development of organ injury in several clinical situations,such as critical diseases,congestive heart failure,and chronic kidney disease.Ultrasonography and abnormal Doppler flow patterns diagnose clinically significant systemic venous congestion.Cardiologists and nephrologists might use this valuable,noninvasive,bedside diagnostic tool to establish fluid status and guide clinical choices.

Road Traffic Monitoring from Aerial Images Using Template Matching and Invariant Features

Road traffic monitoring is an imperative topic widely discussed among researchers.Systems used to monitor traffic frequently rely on cameras mounted on bridges or roadsides.However,aerial images provide the flexibility to use mobile platforms to detect the location and motion of the vehicle over a larger area.To this end,different models have shown the ability to recognize and track vehicles.However,these methods are not mature enough to produce accurate results in complex road scenes.Therefore,this paper presents an algorithm that combines state-of-the-art techniques for identifying and tracking vehicles in conjunction with image bursts.The extracted frames were converted to grayscale,followed by the application of a georeferencing algorithm to embed coordinate information into the images.The masking technique eliminated irrelevant data and reduced the computational cost of the overall monitoring system.Next,Sobel edge detection combined with Canny edge detection and Hough line transform has been applied for noise reduction.After preprocessing,the blob detection algorithm helped detect the vehicles.Vehicles of varying sizes have been detected by implementing a dynamic thresholding scheme.Detection was done on the first image of every burst.Then,to track vehicles,the model of each vehicle was made to find its matches in the succeeding images using the template matching algorithm.To further improve the tracking accuracy by incorporating motion information,Scale Invariant Feature Transform(SIFT)features have been used to find the best possible match among multiple matches.An accuracy rate of 87%for detection and 80%accuracy for tracking in the A1 Motorway Netherland dataset has been achieved.For the Vehicle Aerial Imaging from Drone(VAID)dataset,an accuracy rate of 86%for detection and 78%accuracy for tracking has been achieved.

Pedestrian flow through exit:Study focused on evacuation pattern

Experiments are conducted on the evacuation rate of pedestrians through exits with queued evacuation pattern and random evacuation pattern. The experimental results show that the flow rate of pedestrians is larger with the random evacuation pattern than with the queued evacuation pattern. Therefore, the exit width calculated based on the minimum evacuation clear width for every 100 persons, which is on the assumption that the pedestrians pass through the exit in one queue or several queues, is conservative. The number of people crossing the exit simultaneously is greater in the random evacuation experiments than in the queued evacuation experiments, and the time interval between the front row and rear row of people is shortened in large-exit conditions when pedestrians evacuate randomly. The difference between the flow rate with a queued evacuation pattern and the flow rate with a random evacuation pattern is related to the surplus width of the exit, which is greater than the total width of all accommodated people streams. Two dimensionless quantities are defined to explore this relationship. It is found that the difference in flow rate between the two evacuation patterns is stable at a low level when the surplus width of the exit is no more than 45% of the width of a single pedestrian stream. There is a great difference between the flow rate with the queued evacuation pattern and the flow rate with the random evacuation pattern in a scenario with a larger surplus width of the exit. Meanwhile, the pedestrians crowd extraordinarily at the exit in these conditions as well, since the number of pedestrians who want to evacuate through exit simultaneously greatly exceeds the accommodated level. Therefore, the surplus width of exit should be limited especially in the narrow exit condition, and the relationship between the two dimensionless quantities mentioned above could provide the basis to some extent.

A divergent pattern in functional connectivity: a transdiagnostic perspective

Functional magnetic resonance imaging(fMRI)is a popular tool used to investigate not only how the brain responds to specific stimuli during sensorimotor or cognitive tasks,but also brain activity at rest.The physics beyond this approach is based on the analysis of the blood oxygenation level-dependent signal.

Feature Matching via Topology-Aware Graph Interaction Model

Feature matching plays a key role in computer vision. However, due to the limitations of the descriptors, the putative matches are inevitably contaminated by massive outliers.This paper attempts to tackle the outlier filtering problem from two aspects. First, a robust and efficient graph interaction model,is proposed, with the assumption that matches are correlated with each other rather than independently distributed. To this end, we construct a graph based on the local relationships of matches and formulate the outlier filtering task as a binary labeling energy minimization problem, where the pairwise term encodes the interaction between matches. We further show that this formulation can be solved globally by graph cut algorithm. Our new formulation always improves the performance of previous localitybased method without noticeable deterioration in processing time,adding a few milliseconds. Second, to construct a better graph structure, a robust and geometrically meaningful topology-aware relationship is developed to capture the topology relationship between matches. The two components in sum lead to topology interaction matching(TIM), an effective and efficient method for outlier filtering. Extensive experiments on several large and diverse datasets for multiple vision tasks including general feature matching, as well as relative pose estimation, homography and fundamental matrix estimation, loop-closure detection, and multi-modal image matching, demonstrate that our TIM is more competitive than current state-of-the-art methods, in terms of generality, efficiency, and effectiveness. The source code is publicly available at http://github.com/YifanLu2000/TIM.

Pig Reproductive and Respiratory Syndrome Virus (PRRSV) Does Not Attach to Boar Sperm;It Affects Only the Velocity Pattern and the Mobility Pattern

The purpose of the study was to evaluate the sperm viability of semen infected with PRRSV viral particles, observing the effect of the Virus on the motility of boar sperm. The work was carried out at the FMVZ-BUAP Genetics and Reproduction Laboratory. 5 stallions were used. Each sample contained 1 × 106 sperm, the PRRS virus strain was ATCC-VR-2332 (0, 102, 104 and 106 copies of RNA/mL in triplicate), it was observed daily at the CASA;Hamilton Thorne®. Cells with MT (P < 0.05) on days 1, 3, 5, 7 and 10 of evaluation with 201 ± 7.3, 167 ± 10.1, 165 ± 14.6, 134 ± 8.2 and 120 ± 8.8, respectively. The % MP between control and virus concentrations (P ≥ 0.05). The LCV on day 1 and 7 PI at 10X2 and 10X6 (P < 0.05) vs control. In the Correlation Matrix, where it is observed that there is a correlation between VSL and VAP, VSL and VCL, VCL and ALH, VAP with ALH. There is a correlation of VSL and ALH, STR and ALH. In this study there were (P ≤ 0.01) in the VCL, in the concentrations (102) 162.81 ± 10.65 and (106) 177.12 ± 5.77 vs 193.04 ± 4.62 of control. This indicates that altering these parameters would be related to fertility and the PRRS virus affects the LCV. Regarding the VSL, it was observed that the sperm infected with viruses 102, 104 and 106 of 48.00 ± 3.38, 49.88 ± 1.83 and 50.55 ± 2.24 Vs. 56.66 ± 1.68 of control respectively, the control would have greater possibilities of fertilizing the oocyte. In this study, it was found (P ≤ 0.01) in the VAP with 102 of 77.26 ± 5.16, 104 with 83.35 ± 2.41 and 106 with 81.29 ± 3.14 vs the control with 90.56 ± 2.07. Regarding the ALH there is (P < 0.05) a 104 with 8.70 ± .26 and 106 with 9.64 ± 0.23 vs control 8.50 ± 0.27. The presence of different concentrations of PRRSV in boar semen induces changes in different types of sperm motility. Infection of ejaculates with the PRRS virus affects sperm motility on days 1, 3, 5, 7, and 10 post-infections.

Multiple Matching Attenuation Based on Curvelet Domain Extended Filtering

The paper develops a multiple matching attenuation method based on extended filtering in the curvelet domain,which combines the traditional Wiener filtering method with the matching attenuation method in curvelet domain.Firstly,the method uses the predicted multiple data to generate the Hilbert transform records,time derivative records and time derivative records of Hilbert transform.Then,the above records are transformed into the curvelet domain and multiple matching attenuation based on least squares extended filtering is performed.Finally,the attenuation results are transformed back into the time-space domain.Tests on the model data and field data show that the method proposed in the paper effectively suppress the multiples while preserving the primaries well.Furthermore,it has higher accuracy in eliminating multiple reflections,which is more suitable for the multiple attenuation tasks in the areas with complex structures compared to the time-space domain extended filtering method and the conventional curvelet transform method.

Study on Epidemiological Profile, Clinical Profile, and Angiographic Patterns in Acute Coronary Syndrome Patients in a Tertiary Health Care Center in Haryana

Background: Cardiovascular diseases are the leading cause of death in India, with coronary artery disease (CAD) accounting for a majority of the deaths. There are few large registries on acute coronary syndrome (ACS) from India. Our aim is to study the clinical and epidemiological profile of ACS PATIENTS presenting to our institute, including their angiographic features. Methods: This hospital-based observational, single tertiary care center, prospective study was conducted on patients admitted in the Department of Cardiology at a tertiary care center in Haryana. The study included 400 patients aged greater than 18 years who were admitted with the diagnosis of ACS, and it was carried out for 1 year. The epidemiological profile, clinical history, risk factors, electrocardiogram findings, and angiographic pattern were studied and analyzed with appropriate statistical tools. Results: The mean age of the study population was 55.12 ± 11.78 years. Male and female ratio was 2.4:1. The majority of the patients came from rural background (80%);24% of the patients were illiterate. Smoking was the most common risk factor (51.5%) in our study population followed by hypertension (40%) and diabetes (28%). Unstable angina was the most common type of ACS, which was found in 68.25% of patients. Premature CAD was found in 27.8% of patients and obstructive CAD was found in 63% of patients. Coronary angiography revealed that 39% had single vessel disease (SVD), 23.5% had double vessel disease (DVD), and 27.5% had triple vessel disease (TVD). LAD was more commonly involved, followed by RCA and LCX. Within the first 24 hours, 67% of patients sought medical assistance and only 38.5% received definitive treatment, suggesting a delay in seeking definitive treatment in our study population. Conclusion: The study suggests that unstable angina is the most common form of ACS in the study population, which is mostly of rural background with significant delay in seeking medical help. Smoking is the most common risk factor in the study population.

Pattern of Referral of Obstetric Patients at a Tertiary Care Hospital in Southern Nigeria

Background: Health challenges that are difficult to manage at primary health centres should be referred to secondary health facilities, and if untreated, to the tertiary hospitals. A good referral should include the patient’s biography, such as age, gender, tribe, religion, occupation, medical history, the reason for the referral, treatments received, and clinical diagnosis. Objectives: To evaluate the referral patterns, indications for referrals, and feto-maternal outcomes for obstetric patients who were referred to the University of Port Harcourt Teaching Hospital. Materials and Methods: A prospective study of patients admitted to the Obstetric unit from January 1, 2021, to December 31, 2022. Data was collected from patients while on admission or clinic visits and recorded in an excel spread sheet. Data was analyzed with the Statistical Package for Social Sciences (SPSS) version 25. Results: Of the 3469 patients were admitted to the obstetric unit, 1476 and 1993 were admitted in 2021 and 2022, respectively. Most (70.35%) of the patients were in the 20-34 years age group, parity 1-4 was the most frequent (66.49%), while 85.39% of patients were booked. 10.46% of the booked patients were referred from other facilities, whereas 89.54% of patients were booked at our facility from the onset. Most common indications of referrals were previous caesarean section (CS) at term (40.09%) and hypertensive disorders of pregnancy (17.59%). The outcome for 2021 indicated 17 maternal deaths, 132 fetal deaths and 1010 live births, giving maternal mortality ratio (MMR) as 1810.44 per 100,000 live births and perinatal mortality ratio (PMR) of 130.7 per 1000 births respectively. In 2022, there were 17 maternal deaths, 130 fetal deaths and 1297 deliveries, giving a MMR of 1399 per 100,000 live births and a PMR of 100.2 per 1000 births. Conclusion: The pattern of referral among obstetric patients in this study shows that a lot of the patients do not get adequate care at the lower cadre of the referral system, hence adequate facilities should be made available in primary and secondary health centres to tackle obstetric emergencies.

Perfect 1-k Matchings of Bipartite Graphs

Let k be a positive integer and G a bipartite graph with bipartition (X,Y). A perfect 1-k matching is an edge subset M of G such that each vertex in Y is incident with exactly one edge in M and each vertex in X is incident with exactly k edges in M. A perfect 1-k matching is an optimal semi-matching related to the load-balancing problem, where a semi-matching is an edge subset M such that each vertex in Y is incident with exactly one edge in M, and a vertex in X can be incident with an arbitrary number of edges in M. In this paper, we give three sufficient and necessary conditions for the existence of perfect 1-k matchings and for the existence of 1-k matchings covering | X |−dvertices in X, respectively, and characterize k-elementary bipartite graph which is a graph such that the subgraph induced by all k-allowed edges is connected, where an edge is k-allowed if it is contained in a perfect 1-k matching.

Tuning the diffusion constant to optimize the readout of positional information of spatial concentration patterns

Positional information encoded in spatial concentration patterns is crucial for the development of multicellular organisms.However,it is still unclear how such information is affected by the physically dissipative diffusion process.Here we study one-dimensional patterning systems with analytical derivation and numerical simulations.We find that the diffusion constant of the patterning molecules exhibits a nonmonotonic effect on the readout of the positional information from the concentration patterns.Specifically,there exists an optimal diffusion constant that maximizes the positional information.Moreover,we find that the energy dissipation due to the physical diffusion imposes a fundamental upper limit on the positional information.

A Non-Parametric Scheme for Identifying Data Characteristic Based on Curve Similarity Matching

For accurately identifying the distribution charac-teristic of Gaussian-like noises in unmanned aerial vehicle(UAV)state estimation,this paper proposes a non-parametric scheme based on curve similarity matching.In the framework of the pro-posed scheme,a Parzen window(kernel density estimation,KDE)method on sliding window technology is applied for roughly esti-mating the sample probability density,a precise data probability density function(PDF)model is constructed with the least square method on K-fold cross validation,and the testing result based on evaluation method is obtained based on some data characteristic analyses of curve shape,abruptness and symmetry.Some com-parison simulations with classical methods and UAV flight exper-iment shows that the proposed scheme has higher recognition accuracy than classical methods for some kinds of Gaussian-like data,which provides better reference for the design of Kalman filter(KF)in complex water environment.

Distributed Matching Theory-Based Task Re-Allocating for Heterogeneous Multi-UAV Edge Computing

Many efforts have been devoted to efficient task scheduling in Multi-Unmanned Aerial Vehicle(UAV)edge computing.However,the heterogeneity of UAV computation resource,and the task re-allocating between UAVs have not been fully considered yet.Moreover,most existing works neglect the fact that a task can only be executed on the UAV equipped with its desired service function(SF).In this backdrop,this paper formulates the task scheduling problem as a multi-objective task scheduling problem,which aims at maximizing the task execution success ratio while minimizing the average weighted sum of all tasks’completion time and energy consumption.Optimizing three coupled goals in a realtime manner with the dynamic arrival of tasks hinders us from adopting existing methods,like machine learning-based solutions that require a long training time and tremendous pre-knowledge about the task arrival process,or heuristic-based ones that usually incur a long decision-making time.To tackle this problem in a distributed manner,we establish a matching theory framework,in which three conflicting goals are treated as the preferences of tasks,SFs and UAVs.Then,a Distributed Matching Theory-based Re-allocating(DiMaToRe)algorithm is put forward.We formally proved that a stable matching can be achieved by our proposal.Extensive simulation results show that Di Ma To Re algorithm outperforms benchmark algorithms under diverse parameter settings and has good robustness.

Heparin-binding protein as a predictor of mortality in patients with diabetes mellitus and community-acquired pneumonia in intensive care unit:a propensity score matched study

BACKGROUND:Patients with diabetes mellitus(DM)are vulnerable to community-acquired pneumonia(CAP),which have a high mortality rate.We aimed to investigate the value of heparin-binding protein(HBP)as a prognostic marker of mortality in patients with DM and CAP.METHODS:This retrospective study included CAP patients who were tested for HBP at intensive care unit(ICU)admission from January 2019 to April 2020.Patients were allocated to the DM or non-DM group and paired with propensity score matching.Baseline characteristics and clinical outcomes up to 90 days were evaluated.The primary outcome was the 10-day mortality.Receiver operating characteristic(ROC)curves,Kaplan-Meier analysis,and Cox regression were used for statistical analysis.RESULTS:Among 152 enrolled patients,60 pairs were successfully matched.There was no significant difference in 10-day mortality,while more patients in the DM group died within 28 d(P=0.024)and 90 d(P=0.008).In the DM group,HBP levels at ICU admission were higher in 10-day non-survivors than in 10-day survivors(median 182.21[IQR:55.43-300]ng/ml vs.median 66.40[IQR:34.13-107.85]ng/mL,P=0.019),and HBP levels could predict the 10-day mortality with an area under the ROC curve of 0.747.The cut-off value,sensitivity,and specificity were 160.6 ng/mL,66.7%,and 90.2%,respectively.Multivariate Cox regression analysis indicated that HBP was an independent prognostic factor for 10-day(HR 7.196,95%CI:1.596-32.455,P=0.01),28-day(HR 4.381,95%CI:1.449-13.245,P=0.009),and 90-day mortality(HR 4.581,95%CI:1.637-12.819,P=0.004)in patients with DM.CONCLUSION:Plasma HBP at ICU admission was associated with the 10-day,28-day,and 90-day mortality,and might be a prognostic factor in patients with DM and CAP.

Temporal and spatial evolution of global major grain trade patterns

The complex and volatile international landscape has significantly impacted global grain supply security. This study uses a complex network analysis model to examine the evolution and trends of the global major grain trade from 1990 to 2020, focusing on network topology, centrality ranking, and community structure. There are three major findings. First, the global major grain trade network has expanded in scale, with a growing emphasis on diversification and balance. During the study period, the United States, Canada, China, and Brazil were the core nodes of the network. Grain-exporting countries were mainly situated in Asia, the Americas, and Europe, and importing countries in Asia, Africa, and Europe. Second, a significant increase in the number of high centrality countries with high export capacity occurred, benefiting from natural advantages such as fertile land and favorable climates. Third, the main global grain trade network is divided into four communities, with the Americas-Europe community being the largest and most widespread. The formation of the community pattern was influenced by geographic proximity, driven by the core exporting countries. Therefore, the world needs to enhance the existing trade model, promote the multi-polarization of the grain trade network, and establish a global vision for the future community. Countries and regions should participate actively in global grain trade security governance and institutional reform, expand trade links with other countries, and optimize import and export policies to reduce trade risks.