Miracle-dz/UniFAR-FTUs huggingface dataset:
Deterministic hierarchical joint remote state preparation with six-particle partially entangled state

In this paper, we present a novel scheme for hierarchical joint remote state preparation (HJRSP) in a deterministic manner, where two senders can jointly and remotely prepare an arbitrary single-qubit at three receivers’ port. A six-particle partially entangled state is pre-shared as the quantum channel. There is a hierarchy among the receivers concerning their powers to reconstruct the target state. Due to various unitary operations and projective measurements, the unit success probability can always be achieved irrespective of the parameters of the pre-shared partially entangled state.
A morphology-based method for building change detection using multi-temporal airborne LiDAR data

ABSTRACT The detection of building changes plays an important role for land management and urban planning. This study proposes an automatic method that applies the morphology-based method for detection of building changes with multi-temporal airborne Light Detection and Ranging (LiDAR) data. In this method, three types of land use are classified as ground, building and vegetation by Triangulated Irregular Network (TIN) filter and Support Vector Machine (SVM) with the two sets of point clouds acquired at different times. Thereafter, the morphological algorithm is applied to distinguish the changed buildings from trees, which significantly reduces the identification of errors. The changed building objects are classified as three types: ‘newly built’, ‘taller’ and ‘demolished’, with the use of rule analysis. The case study area is located in Liujia village, Shenyang, China. The two sets of LiDAR test data were acquired by Leica ALS 60 (3 points/km2) and ALS 80 (15 points/km2) from September 2014 and February 2017, respectively. Field investigation proves that the accuracy of the identified changed buildings of ‘newly built’, ‘demolished’ and ‘taller’ are 95.4%, 92.9% and 100%. The proposed method has the advantages of high accuracy and reliability, which will provide a reference for the detection of building changes.
Triangulation of simple arbitrarily shaped polyhedra by cutting off one vertex at a time

We describe a heuristic method of triangulating arbitrarily shaped polyhedra without the addition of Steiner points. The polyhedra are simple, with each vertex connected to at least 3 other vertices (ie, coplanarity and colinearity are not considered). They may, however, be convex or concave and consist of dozens or even hundreds of facets. This makes the treatment universal enough to well meet the requirements of models used to simulate fractured rock masses. Certain concepts are defined in the work, eg, adjacent vertices, polygon of adjacent vertices, and closed cone of a vertex. A polygon of adjacent vertices of an apex can be subdivided into a set of nonoverlapping triangles without adding any vertices. These triangles, together with the apex, form tetrahedra whose union is the closed cone of the apex. The polyhedron is thus the union of the closed cones. Subsequently, we triangulate the polyhedron by gradually removing the closed cones of its vertices. The number of vertices of the polyhedron decreases by one each time a closed cone is removed. A block with n vertices can produce no more than n−3 tetrahedra. We present the analysis procedure and discuss the core issues of the method proposed.
Direct Synthesis of Iterative Algorithms With Bounds on Achievable Worst-Case Convergence Rate

Iterative first-order methods such as gradient descent and its variants are widely used for solving optimization and machine learning problems. There has been recent interest in analytic or numerically efficient methods for computing worst-case performance bounds for such algorithms, for example over the class of strongly convex loss functions. A popular approach is to assume the algorithm has a fixed size (fixed dimension, or memory) and that its structure is parameterized by one or two hyper-parameters, for example a learning rate and a momentum parameter. Then, a Lyapunov function is sought to certify robust stability and subsequent optimization can be performed to find optimal hyperparameter tunings. In the present work, we instead fix the constraints that characterize the loss function and apply techniques from robust control synthesis to directly search over algorithms. This approach yields stronger results than those previously available, since the bounds produced hold over algorithms with an arbitrary, but finite, amount of memory rather than just holding for algorithms with a prescribed structure.
Optimized acousto-optic modulation for the V-type electromagnetically induced transparency in rubidium-87 D1 line

We present an experimental setup of optimized acousto-optic modulator designed for observing a V-type electromagnetically induced transparency resonance in the D1 line of rubidium-87, with the full width at half maximum being equal to 2.7 MHz. Possible artefacts and undesirable influences on the signal resulting from this method are discussed in detail. The solutions to such technical challenges as beam steering and intensity fluctuations are found in optimization of optical setup. The reported method offers a number of advantages such a single external-cavity diode laser to create a bichromatic optical field outside the laser, whereby both the coupling and probe beams have identical properties. Moreover, the both beams are equally affected by environmental perturbations to the laser. Subsequently, the influence of mode hopping, beam-power fluctuation and frequency drift on the resonance can be eliminated. This negates a need in complicated and expensive temperature and current stabilizations, as well as in a locking unit. The simplicity and stability of the improved setup make our method suitable for many applications based upon electromagnetically induced transparency, especially those in the field of precision measurements.
Characteristics of Ordinal Data in Trend Odds Model

Ordinal data widely appear in many scientific areas, are often assumed with proportional odds in ordinal logistic regression. When the ordinal data have monotone manner across cut-points, proportional odds assumption become less appropriate. The lack of proportionality may be possible captured using trend odds model which have constrained structural relationship between the odds and the cut-points. This paper describes briefly cumulative odds which are the foundation of trend odds model and demonstrates algebraically the trend odds model related to latent logistic and uniform distribution to obtain the explicit form of slope of the trend. A data set is used to illustrate the interpretation of trend odds model, we apply this model to cigarettes consumption which has monotone manner across cut-points that seems the proportional assumption is more likely not appropriate. However, characteristic of ordinal data that fit trend odds model properly must be specified because only monotone manner is insufficient. We perform simulation using PROC NLMIXED in SAS system and find that ordinal data must significantly monotone for unexposed group and the ratio between covariates is higher for higher level cut-points.
Secure and secret cooperation of robotic swarms by using Merkle trees

Swarm robotics systems are envisioned to become an important component of both academic research and real-world applications. However, in order to reach widespread adoption, new models that ensure the secure cooperation of these systems need to be developed. This work proposes a novel model to encapsulate cooperative robotic missions in Merkle trees, one of the fundamental components of blockchain technology. With the proposed model, swarm operators can provide the "blueprint" of the swarm's mission without disclosing raw data about the mission itself. In other words, data verification can be separated from data itself. We propose a system where swarm robots have to "prove" their integrity to their peers by exchanging cryptographic proofs. This work analyzes and tests the proposed approach for two different robotic missions: foraging (where robots modify the environment) and maze formation (where robots become part of the environment). In both missions, robots were able to cooperate and carry out sequential operations in the correct order without having explicit knowledge about the mission's high-level goals or objectives. The performance, communication costs, and information diversity requirements for the proposed approach are analyzed. Finally, conclusions are drawn and future work directions are suggested.
Aggregation of Sentinel-2 time series classifications as a solution for multitemporal analysis

The general aim of this work was to elaborate efficient and reliable aggregation method that could be used for creating a land cover map at a global scale from multitemporal satellite imagery. The study described in this paper presents methods for combining results of land cover/land use classifications performed on single-date Sentinel-2 images acquired at different time periods. For that purpose different aggregation methods were proposed and tested on study sites spread on different continents. The initial classifications were performed with Random Forest classifier on individual Sentinel-2 images from a time series. In the following step the resulting land cover maps were aggregated pixel by pixel using three different combinations of information on the number of occurrences of a certain land cover class within a time series and the posterior probability of particular classes resulting from the Random Forest classification. From the proposed methods two are shown superior and in most cases were able to reach or outperform the accuracy of the best individual classifications of single-date images. Moreover, the aggregations results are very stable when used on data with varying cloudiness. They also enable to reduce considerably the number of cloudy pixels in the resulting land cover map what is significant advantage for mapping areas with frequent cloud coverage.
Parameters and AB 0 Blood Groups in Patients with Ovarian Hyperstimulation Syndrome ( OHSS )

Purpose: Ovarian hyperstimulation syndrome (OHSS) is a complication during ovarian stimulation. Patients with moderate and severe OHSS usually require inpatient or intensive-care support. There are scarce data regarding the course of laboratory parameters and no data concerning AB0 blood groups in patients with OHSS. Material and Methods: 174 patients with OHSS were hospitalized in the period of January 2000 to December 2005. Morbidity, pregnancy rate, course of laboratory parameters, blood groups and treatment options were collated. Frequency of AB0 blood groups were compared with 3 distinct control groups. Results: Of 174 patients 32 had OHSS grade I, 71 grade II and 71 severe grade III. 40.8% of all patients had a clinical pregnancy. The most frequent symptoms were ascites, pain and abdominal tension. Almost all patients received infusion therapy with anticoagulation. 20 – 50% were treated with diuretics, analgesics or required ascites drainage. Highly significant changes of laboratory parameters in the course stationary treatment were found. Comparing blood group subtypes to the control groups revealed an increased risk to develop OHSS for non-0 or blood group A. The calculated odds ratios (OR) were between 1.52 and 1.65. These findings were significant or nearly significant. Conclusion: The morbidity of women suffering from OHSS is high, with marked changes in laboratory findings. Treatment options comprise intravenous therapy with crystalloids, fluid balancing, anticoagulation and ascites drainage. There is evidence that determination of AB0 blood groups may be a helpful tool to identify women with a predisposition for OHSS undergoing IVF treatment. Zusammenfassung !
SNIG Property of Matrix Low-Rank Factorization Model

Recently, the matrix factorization model attracts increasing attentions in handling large-scale rank minimization problems, which is essentially a nonconvex minimization problem. Speciﬁcally, it is a quardratic least squares problem and consequently a quartic polynomial optimization problem. In this paper, we introduce a concept of the SNIG (“Second-order Necessary optimality Implies Global optimality”) condition which stands for the property that any second-order stationary point of the matrix factorization model must be a global minimizer. Some scenarios under which the SNIG condition holds are presented. Furthermore, we illustrate by an example when the SNIG condition may fail.
The layout of the radiation shielding of the CSPEC neutron time-of-flight spectrometer at ESS — a Monte Carlo study

At the European Spallation Source (ESS) the neutron time-of-flight spectrometer CSPEC (Cold Chopper Spectrometer) is under construction. In order to keep the background radiation level low for neighboring instruments and to meet the radiation protection requirements of the facility, a radiation shielding around the spectrometer is necessary. For optimization and planning of the radiation shielding, Monte Carlo simulations were carried out by help of the Monte Carlo codes MCNP6 and McStas. The necessary shielding thickness as well as the influence of gaps, breakthroughs, doors, different samples, a beam catcher and Bragg reflections were determined by simulations. The choice of the shielding material (ordinary concrete) is described. The influence of variations in the concrete composition on the dose rate was examined. It is shown that γ-radiation from neutron capture reactions is in all cases the dominant contribution to the dose rate outside the shielding. The simulation results for the final version of the instrument shielding are presented in this paper.
Effect of amphiphilic polymers and sodium alginate on the activity of methylene blue in photogeneration of singlet oxygen 1О2

The influence of amphiphilic polymers (APs): poly-N-vinylpyrrolidone, polyethylene glycol and pluronics F127, F108, as well as sodium alginate (SA) on the activity of methylene blue (MB) in the photogeneration of singlet oxygen 1О2, specifically, in a model photooxidation reaction of tryptophan in water was studied. It was shown that in the presence of all the above-mentioned AP, an increase in the effective rate constant (k eff) of tryptophan photooxidation is observed. It was suggested that the observed effect is associated with the interaction of MB with APs, which leads to disaggregation of dye associates. Such disaggregation leads to an increase in the optical density and intensity of MB luminescence. It was also shown that the photocatalytic activity of MB decreases by a factor of 1.5–3.5 in the presence of SA, which is due to the ionic interaction of the cationic MB with polyanionic SA. The interaction of MB with polysaccharide is confirmed by changes in the absorption and fluorescence spectra of the dye. The introduction of APs into a solution containing MB and SA prevents the interaction between MB and polysaccharide, which leads to an increase in the k eff values of tryptophan photooxidation in the presence of MB-AP-SA system, as well as to an increase in the optical density and fluorescence intensity of MB when AP and SA are added. The existence of weak interactions between the hydrophobic groups of MB molecules and the AP (polyvinylpyrrolidone) is also evidenced by the data obtained through 1H-NMR spectroscopy and the degree of MB fluorescence anisotropy. The AFM method shows the change in the surface structure of a thin film obtained by evaporating an aqueous solution of MB-F108-SA compared to the corresponding structure of a film obtained by evaporating an aqueous solution of MB-SA. MB-AP and MB-AP-SA systems may be promising for practical application in the aPDT treatment of chronic microbial superficial infections.
COWAVE: A labelled COVID-19 wave dataset for building predictive models

The ongoing COVID-19 pandemic has posed a significant global challenge to healthcare systems. Every country has seen multiple waves of this disease, placing a considerable strain on healthcare resources. Across the world, the pandemic has motivated diligent data collection, with an enormous amount of data being available in the public domain. In this manuscript, we collate COVID-19 case data from around the world (available on the World Health Organization (WHO) website), and provide various definitions for waves. Using these definitions to define labels, we create a labelled dataset, which can be used while building supervised learning classifiers. We also use a simple eXtreme Gradient Boosting (XGBoost) model to provide a minimum standard for future classifiers trained on this dataset and demonstrate the utility of our dataset for the prediction of (future) waves. This dataset will be a valuable resource for epidemiologists and others interested in the early prediction of future waves. The datasets are available from https://github.com/RamanLab/COWAVE/.
Preoperative D-dimer Value and Lower Limb Venous Ultrasound for Deep Venous Thrombosis Prevents Postoperative Symptomatic Venous Thromboembolism in Patients Undergoing Colorectal Surgery: A Retrospective Study

Objectives: Preoperative deep venous thrombosis (DVT) can cause potentially life-threatening postoperative venous thromboembolism (VTE). Lower limb venous ultrasound (LLVU) is a modality that can detect DVT. However, the threshold for performing preoperative LLVU in the population undergoing colorectal resection is controversial. In this context, we evaluated whether a preoperative D-dimer value can identify patients who benefit from LLVU from the perspective of preventing postoperative symptomatic VTE. Methods: Patients undergoing colorectal resection in our institute from 2013 to 2020 were retrospectively enrolled (n=2071). We divided the patients into two groups: the clinical indication group (CG: including patients from 2013 to 2016, n=875) and the D-dimer-orientated group (DG: including patients from 2017 to 2020, n=1196). In the CG, LLVU was performed when DVT was clinically suspected; in the DG, preoperative LLVU was performed in patients with a preoperative D-dimer>1.0 μg/ml. Results: In the surveyed period, 277 LLVUs were performed, among which DVT was detected in 34 cases (12.3%). In the CG, DVT was detected in 0.7% of patients, whereas in the DG, it was detected in 2.3% of patients. Postoperative symptomatic VTE was significantly reduced in the DG at both 3 and 6 months after surgery (p=0.041 and 0.020, respectively). Moreover, Multivariate analysis showed that a past medical history of PE and treatment following the CG protocol were independent risk factors for postoperative symptomatic VTE within 6 months of surgery (p<0.0001 and =0.036, respectively). Conclusions: LLVU in patients with a preoperative D-dimer>1.0 μg/ml is a useful method to prevent postoperative symptomatic VTE.
Association of mental health conditions and functional gastrointestinal disorders among Vietnamese new-entry medical students

Background Functional gastrointestinal disorders (FGIDs), also known as disorders of gut-brain interaction, occur not only in the elderly but also in young adults. This study aimed to evaluate the association between mental health conditions and FGIDs among Vietnamese new-entry medical students. Methods This cross-sectional study was conducted in February 2022 among new-entry medical students in Ho Chi Minh City, Vietnam. A printed questionnaire was distributed to all students on the day of freshmen health screening. Their urine samples were collected to screen for Helicobacter pylori infection using rapid urinary test. FGIDs were diagnosed using ROME IV criteria. Gastroesophageal reflux disease (GERD) was defined as the presence of typical reflux symptoms at least twice a week. Mental health conditions, including generalized anxiety disorder (GAD) and major depressive disorder (MDD), were identified using Generalized Anxiety Disorder Assessment-7 (GAD-7) and Patient Health Questionnaire-9 (PHQ-9) scales, respectively. Results Among 400 new-entry medical students who participated in the study, the overall prevalence of FGIDs was 10.3% (functional dyspepsia 6.5%, irritable bowel disease 5.5%). The overlap syndrome (OS) of GERD-FGIDs or different FGIDs was present in 3.0% of participants. The prevalences of GAD and MDD were 6.8% and 10.2%, respectively. The urinary test was positive in 180 (45.0%) participants. In the multivariable logistic regression analysis, MDD was significantly associated with not only the risk of FGIDs (OR = 5.599, 95%CI: 2.173–14.430, p<0.001) but also the risk of OS (OR = 10.076, 95CI%: 2.243–45.266, p = 0.003). Conclusions MDD is associated with FGIDs and OS among new-entry medical students.
A Randomized Trial to Assess the Impact of a Package of Diagnostic Tools and Diagnostic Algorithm on Antibiotic Prescriptions for the Management of Febrile Illnesses Among Children and Adolescents in Primary Health Facilities in Burkina Faso

Abstract Background Low- and middle-income countries face significant challenges in differentiating bacterial from viral causes of febrile illnesses, leading to inappropriate use of antibiotics. This trial aimed to evaluate the impact of an intervention package comprising diagnostic tests, a diagnostic algorithm, and a training-and-communication package on antibiotic prescriptions and clinical outcomes. Methods Patients aged 6 months to 18 years with fever or history of fever within the past 7 days with no focus, or a suspected respiratory tract infection, arriving at 2 health facilities were randomized to either the intervention package or standard practice. The primary outcomes were the proportions of patients who recovered at day 7 (D7) and patients prescribed antibiotics at day 0. Results Of 1718 patients randomized, 1681 (97.8%; intervention: 844; control: 837) completed follow-up: 99.5% recovered at D7 in the intervention arm versus 100% in standard practice (P = .135). Antibiotics were prescribed to 40.6% of patients in the intervention group versus 57.5% in the control arm (risk ratio: 29.3%; 95% CI: 21.8–36.0%; risk difference [RD]: −16.8%; 95% CI: −21.7% to −12.0%; P < .001), which translates to 1 additional antibiotic prescription saved every 6 (95% CI: 5–8) consultations. This reduction was significant regardless of test results for malaria, but was greater in patients without malaria (RD: −46.0%; −54.7% to −37.4%; P < .001), those with a respiratory diagnosis (RD: −38.2%; −43.8% to −32.6%; P < .001), and in children 6–59 months old (RD: −20.4%; −26.0% to −14.9%; P < .001). Except for the period July–September, the reduction was consistent across the other quarters (P < .001). Conclusions The implementation of the package can reduce inappropriate antibiotic prescription without compromising clinical outcomes. Clinical Trials Registration clinicaltrials.gov; NCT04081051.
Mindfulness and loneliness in retired older adults in China: mediation effects of positive and negative affect

Abstract Objectives: Drawing from the mindfulness framework and the broaden-and-build theory, this study investigates the extent to which mindfulness influences loneliness and whether the relation is mediated by positive and negative affect. Method: Data were collected from 748 retired older adults aged 60 and above in Chengdu, China in 2022. Loneliness and mindfulness were measured by the UCLA loneliness scale and by the short-form version of the Five Facet Mindfulness Questionnaire, while the positive and negative affect was assessed by the International Positive and Negative Affect Schedule. Results: The results of this study show that mindfulness was positively associated with positive affect (β = 0.37, p<.001), negatively related to negative affect (β=-0.21, p<.001) and loneliness (β=-0.13, p<.001), and had an indirect effect on loneliness via positive and negative affect (β=-0.20, p<.001). Conclusion: The findings suggest that mindfulness could be a positive resource for improving mental health and reducing loneliness among retired older adults in China.