Miracle-dz/UniFAR-FTUs huggingface dataset:
Visual interpretation of building objects at the initial and final stages of the life cycle according to the satellite and ground survey data

From the point of view of satellite monitoring, construction objects include fixed objects of artificial origin (buildings and structures for various purposes), created from building materials and lying directly on the earth's surface. Someone can conditionally divide the life cycle of a construction object into initial, main and final stages. From the point of view of satellite, ground, aerial photography it is possible to distinguish building objects at the initial, main and final stages from each other. In this case, not all initial stages are exposed to the images, and additional conditions are required to distinguish the final stages in the images (the same applies to the main stages). We can produce the current stage of the life cycle of a building object for various reasons. The paper considers some features of deciphering construction objects at the initial and final stages of their life cycle, primarily in an emergency and abandoned state. Relevant types of construction objects are identified, the structure of decoding signs is determined, and decoding areas are established, we derive the signs themselves for different construction objects. An experiment on the detection of abandoned construction sites on several databases is given.
Hardness of embedding simplicial complexes in $\mathbb {R}^d$

Let EMBED(k,d) be the following algorithmic problem: Given a finite simplicial complex K of dimension at most k, does there exist a (piecewise linear) embedding of K into R^d? Known results easily imply polynomiality of EMBED(k,2) (k=1,2; the case k=1, d=2 is graph planarity) and of EMBED(k,2k) for all k>2 (even if k is not considered fixed). We observe that the celebrated result of Novikov on the algorithmic unsolvability of recognizing the 5-sphere implies that EMBED(d,d) and EMBED(d-1,d) are undecidable for each d>4. Our main result is NP-hardness of EMBED(2,4) and, more generally, of EMBED(k,d) for all k,d with d>3 and d\geq k \geq (2d-2)/3. These dimensions fall outside the so-called metastable range of a theorem of Haefliger and Weber, which characterizes embeddability using the deleted product obstruction. Our reductions are based on examples, due to Segal, Spie\. z, Freedman, Krushkal, Teichner, and Skopenkov, showing that outside the metastable range the deleted product obstruction is not sufficient to characterize embeddability.
FACTORS INFLUENCING THE PURCHASE INTENTION OF HEALTH INSURANCE IN KOTA KINABALU SABAH

Health and life insurance have been very critical issue in today’s world. Insurance has become a major necessity for everyone to have in order to protect them or their family from any unforeseen circumstances in life. This study is done to find out what is the factors that influencing the purchase of health and life insurance to the public as well as to determine the relationship among these variables. This descriptive and quantitative study uses 200 respondents selected using a random sampling method from clients of CIMB Bank Branches around Kota Kinabalu, Sabah. IBM SPSS 23.0 was used to analyse data gathered from a self-administered questionnaire. Findings showed that the intention to purchase was perceived moderately. This study also showed that income level, knowledge level, income protection, risk attitude and social factors are significantly, positively and strongly related to purchase intention of life and health insurance.
Pinning Control Strategy of Multicommunity Structure Networks

In order to investigate the effects of community structure on synchronization, a pinning control strategy is researched in a class of complex networks with community structure in this paper. A feedback control law is designed based on the network community structure information. The stability condition is given and proved by using Lyapunov stability theory. Our research shows that as to community structure networks, there being a threshold , when coupling strength bellows this threshold, the stronger coupling strength corresponds to higher synchronizability; vice versa, the stronger coupling strength brings lower synchronizability. In addition the synchronizability of overlapping and nonoverlapping community structure networks was simulated and analyzed; while the nodes were controlled randomly and intensively, the results show that intensive control strategy is better than the random one. The network will reach synchronization easily when the node with largest betweenness was controlled. Furthermore, four difference networks’ synchronizability, such as Barabasi-Albert network, Watts-Strogatz network, Erdos-Renyi network, and community structure network, are simulated; the research shows that the community structure network is more easily synchronized under the same control strength.
A GNN Architecture With Local and Global-Attention Feature for Image Classification

Convolutional neural network (CNN) is quite popular in computer vision, especially in image classification with excellent performance. However, limited by the convolution kernels, CNN-based classifiers are hard to extract global feature from the original image, while exact object locations in the environment are included in the global feature. One popular way to improve global feature extraction performance is to use graph neural network (GNN) which can aggregate global information through the connection relationship of different nodes. In this work, a novel end-to-end graph neural network architecture is proposed, in which local and global-attention feature are used simultaneously to achieve more accurate predictions. In this architecture, a CNN block is designed to learn local feature and graph convolutional neural network (GCN) is used to learn global feature. Global-attention feature for final prediction is down-sampled from global feature by the proposed global multi-head self-attention pooling (GMSAPool) based on self-attention mechanism, which reconstructs the input graph by introducing virtual node and automatically assigns different weights to each node to obtain a more representative global-attention feature. In addition, the proposed architecture can be trained without converting images to graphs in advance, and the computational burden can also be reduced. This approach is demonstrated on three open datasets (Agricultural Disease, Caltech256 and CIFAR-100) to validate the effectiveness. The determined experimental results showed that: 1) The proposed model achieve 84.46%, 77.80%, and 83.33% on the Macro-F1 in three datasets respectively, improving over the best baselines; 2) Global-attention feature that is more conducive to the final prediction is extracted by GMSAPool from numerous nodes, in which Macro-P,Macro-R and Macro-F1 are respectively improved 3.655%,1.12%,2.715% on average.
Penatalaksanaan Fisioterapi Pada Non-Hemorrhagic Stroke: Studi Kasus

Stroke merupakan defisit neurologis yang terjadi tiba-tiba disebabkan oleh gangguan vaskular. Secara umum, stroke dibagi menjadi 2 yaitu stroke hemoragik dan non hemoragik. Penurunan activity daily living pada pasien stroke menjadi permasalahan dengan penangana jangka panjang pada pasien stroke. Terapi latihan merupakan salah satu metode untuk meningkatkan activity daily living. Penelitian ini bertujuan untuk mengetahui efektifitas terapi latihan terhadap perkembangan activity daily living pada pasien stroke non hemorogik. Penelitian ini menggunakan pendekatan case report. Pemberian terapi latihan yang dilakukan sebanyak 4 kali didapatkan hasil nilai score indeks barthel mengontrol BAB : 1, mengontrol BAK : 0, membersihkan diri : 1, toileting : 1, makan : 3, berpindah tempat : 2, mobilisasi atau berjalan : 2, berpakaian : 2, naik turun tangga : 0, mandi : 0. Terapi latihan yang diberikan pada pasien stroke non hemoregik menujukan hasil yang tidak signifikan pada ADL pasien, akan tetapi menjadi salah satu bentuk penanganan rehabilitasi medik yang dapat dilakukan pada masa golden period.
Role of the surface state in the Kondo resonance width of a Co single adatom on Ag(111)

Q. L. Li,1 C. Zheng,1 R. Wang,1 B. F. Miao,1,2 R. X. Cao,1 L. Sun,1,2 D. Wu,1,2 Y. Z. Wu,2,3 S. C. Li,1,2 B. G. Wang,1,2,* and H. F. Ding1,2,† 1National Laboratory of Solid State Microstructures and Department of Physics, Nanjing University, 22 Hankou Road, Nanjing 210093, People’s Republic of China 2Collaborative Innovation Center of Advanced Microstructures, Nanjing University, 22 Hankou Road, Nanjing 210093, People’s Republic of China 3Department of Physics, Fudan University, 220 Handan Road, Shanghai 200433, People’s Republic of China
Software Packages for Bayesian Multilevel Modeling

Multilevel modeling is a statistical approach to analyze hierarchical data that consist of individual observations nested within clusters. Bayesian method is a well-known, sometimes better, alternative of Maximum likelihood method for fitting multilevel models. Lack of user friendly and computationally efficient software packages or programs was a main obstacle in applying Bayesian multilevel modeling. In recent years, the development of software packages for multilevel modeling with improved Bayesian algorithms and faster speed has been growing. This article aims to update the knowledge of software packages for Bayesian multilevel modeling and therefore to promote the use of these packages. Three categories of software packages capable of Bayesian multilevel modeling including brms, MCMCglmm, glmmBUGS, Bambi, R2BayesX, BayesReg, R2MLwiN and others are introduced and compared in terms of computational efficiency, modeling capability and flexibility, as well as user-friendliness. Recommendations to practical users and suggestions for future development are also discussed.
From IMU Measurement Sequence to Velocity Estimate Sequence: An Effective and Efficient Data-Driven Inertial Odometry Approach

We propose a novel deep-learning-based inertial odometry framework to improve both localization accuracy and efficiency. The measured 3-D accelerations and angular velocities are constructed as two independent channel 2-D features. In each channel, the three axes of accelerations or angular velocities constitute the height dimension, whereas the temporal axis represents the width dimension. In the neural network module, we first employ 2-D convolutional operations to convert the input features to 1-D series with fourfold downsampling along the temporal axis. We then apply the convolutional attention module to refine the generated 1-D feature map and long short-term memory (LSTM) layers to generate the hidden state for each refined time index, which is followed by two separate two-layer multilayer perceptrons (MLPs) to regress the velocity and the uncertainty. During backpropagation, we use the negative log-likelihood loss to optimize the velocity and the uncertainty objectives. Benefiting from the velocity sequence objective in a single network forward propagation procedure, we also add the average squared distance between the ground-truth relative position and that of the prediction to minimize the location error. Extensive experiments on both the robust neural inertial navigation (RoNIN) dataset and the real scenario collected data in the CUHK campus show higher localization accuracy with 10 times higher efficiency of the proposed framework than the comparing methods.
ANTIMICROBIAL SUSCEPTIBILITY PATTERNS OF PSEUDOMONAS AEUROGINOSA ISOLATED FROM PATIENTS WITH RESPIRATORY DISEASES IN A TERTIARY CARE HOSPITAL

Antimicrobial medicines have been extensively used since ancient times to treat various microbial infections, many of which can be life-threatening and contribute significantly to healthcare expenses worldwide. However, the increasing adaptability of these antibiotics has led to the emergence of resistance among microorganisms. This study aims to investigate the prevalence and susceptibility patterns of Pseudomonas aeruginosa among patients with respiratory disorders in a tertiary healthcare setting. A cross-sectional study was conducted at Civil Hospital Sialkot from September 2021 to June 2022, where 500 sputum samples were collected from both in and out-patients. Samples were collected following standard protocols and subjected to inoculation. Isolates were identified using standard biochemical protocols, and their antibiotic susceptibility patterns were determined using the Clinical and Laboratory Standards Institute (CLSI) guidelines and Kirby-Bauer's disc diffusion method. Out of the 500 sputum samples collected, 206 (41.2%) showed growth of microorganisms. Of these, 77 (37.38%) were identified as Pseudomonas aeruginosa. The isolates comprised 54.5% males and 45.5% females, with a mean age of 54.77 ± 11.16. The highest sensitivity was observed for Amikacin (93.5%), followed by Meropenem (92.21%), while the lowest sensitivity was observed for Cefoperazone (18.18%) and Tazocin (16.89%). Similarly, maximum resistance was seen in the case of Cefoperazone and Tazocin at (81.82%) and (83.11%) respectively. The results indicate that commonly used antibiotics against Pseudomonas aeruginosa are becoming increasingly resistant, with aminoglycosides and carbapenems remaining the two classes with the highest activity against this microorganism. These findings underscore the need for continued surveillance and appropriate use of antibiotics to minimize the development of resistance.
NEW GENETIC ALGORITHM WITH GREEDY HEURISTIC FOR CLUSTERING PROBLEMS WITH UNKNOWN NUMBER OF GROUPS

In this research, we propose new modification of the genetic algorithm with greedy heuristic witch allows to solve series of clustering problems with unknown number of groups (clusters). The applicability and efficiency of new method is experimentally proved. Achieved results are compared with other algorithms which solve each of problems separately. Experiments show that new algorithm is faster than other methods for various problems.
Research on the construction technology of cardiovascular disease Q&A system based on knowledge graph

Cardiovascular disease is a serious threat to human life and health, with high prevalence, high disability and high mortality. Cardiovascular disease Q&A system is more targeted and reliable than search engines, and users can get more concise and clear information. As a structured data source of the Q&A system, the knowledge graph enhances the flexibility and accuracy of the system. In this paper, knowledge extraction from authoritative medical websites and Baidu Baike using web spiders, knowledge fusion with reference to medical textbooks on cardiovascular diseases, and knowledge storage using Neo4j graph database were used to build the knowledge graph of cardiovascular diseases. On this basis, the Q&A system was built based on template matching and vector parsing methods, using word2vec model, TF-IDF algorithm, Naive Bayes classifier and support vector machine classifier from the perspective of doctors and patients respectively. The experiments showed that the Q&A system can effectively answer most of the questions on cardiovascular diseases.
OJ 287 as a Rotating Helix

We present preliminary data from high-cadence 15-GHz VLBA images of OJ 287 from 1995 to 2015. The ridgelines suggest that the jet is rotating, perhaps with a period of∼30 years. The EVPA of the core rotated by 240° in 2001–2002 and decreased slowly after that. The inner jet apparently moved to a new direction after the rotation,as shown by the emergence of a new component at a new PA at 43 GHz, in 2004. This was presaged by a strong rise in the ﬂux density of the core, and then its sudden fall as the new component was identiﬁed. The equivalent sequence of events took place about 5 years later at 15 GHz, but in addition the core EVPA had a step in 2006 and moved to be aligned with the new 43-GHz component. The 15-GHz core became optically thin in 2006, but the angular resolution was insufﬁcient to separate the new component from the core until 2010
Factor Replication with Industry Stratification

Abstract Factor investing exploits asset pricing anomalies to enhance fund returns. Unlike traditional market capitalization indexes, factors have onerous replication costs. We consider the impact of omitting costly, small stocks by industry in stratified factor-replicating portfolios. Such industry stratification achieves broader industry coverage and lowers tracking error compared with competing approaches. We show that the improvement in tracking error is due to enhanced industry coverage, not risk exposure, resulting in substantial economic benefits.
Scrolling through sleep: Moroccan high school students smartphone uses and sleep quality

In the educational field, sleep is a vital need for students. Recent research has connected smartphone addiction, poor sleep, and academic failure. There is a glaring paucity of information on this subject in Morocco. In order to fill this gap, we conducted this study. This cross-sectional study investigated the effect of smartphone addiction on sleep quality and school outcomes among secondary school students in Marrakesh, Morocco. Following the simple random method, a sample of 389 students was selected. They answered an online questionnaire that included questions about some demographic characteristics, smartphone use, and sleeping habits. The results revealed that 57.8% of the students suffer from smartphone addiction, and 59.9% suffer from poor sleep quality. The study found that there is a moderately positive correlation between smartphone addiction and poor sleep quality. The study not only suggests the need for parents, educators, and health professionals to raise awareness about the negative effects of smartphone addiction on students’ sleep quality, but also provides a basis for developing interventions aims at reducing smartphone addiction and improving sleep quality.
A Study on Ditherless CDR with Optimal Phase Detection

Bang-bang phase detectors are widely used for today’s high-speed communication circuits such as phase-locked loops (PLLs), delay-locked loops (DLLs) and clockand-data recovery loops (CDRs) because it is simple, fast, accurate and amenable to digital implementations. However, its hard nonlinearity poses difficulties in design and analyses of the bang-bang controlled timing loops. Especially, dithering in bang-bang controlled CDRs sets conflicting requirements on the phase adjustment resolution as one tries to maximize the tracking bandwidth and minimize jitter. A fine phase step is helpful to minimize the dithering, but it requires circuits with finer resolution that consumes large power and area. In this background, this dissertation introduces an optimal phase detection technique that can minimize the effect of dithering without requiring fine phase resolution. A novel phase interval detector that looks for a phase interval enclosing the desired lock point is shown to find the optimal phase that minimizes the timing error without dithering. A digitally-controlled, phase-interpolating DLL-based CDR fabricated in 65nm CMOS demonstrates that it can achieve small area of 0.026mm2 and low jitter of 41mUIpp with a coarse phase adjustment step of 0.11UI, while dissipating only 8.4mW at 5Gbps. For the theoretic basis, various analysis techniques to understand bang-bang controlled timing loops are also presented. The proposed techniques are explained for both linearized loop and non-linear one, and applied to the evaluation of the proposed phase detection technique.
Constrained Maximum Likelihood Estimators for Densities

We put forward a framework for nonparametric density estimation in situations where the sample is supplemented by information and assumptions about shape, support, continuity, slope, location of modes, density values, etc. These supplements are incorporated as constraints that in conjunction with a maximum likelihood criterion lead to constrained infinite-dimensional optimization problems that we formulate over spaces of semicontinuous functions. These spaces, when equipped with an appropriate metric, offer a series of advantages including simple conditions for existence of estimators and their limits and, in particular, guarantee the convergence of modes of densities. Relying on the approximation theory---epi-convergence---for optimization problems, we provide general conditions under which estimators subject to essentially arbitrary constraints are consistent and illustrate the framework with a number of examples that span classical and novel shape constraints.
Microbes as a gift from God

he wonder and unseen organisms, microbes are tiny creatures, which are not visible to the naked eye. Microorganisms are ubiquitous in nature and known to exist everywhere from the equator to poles, deserts to deep sea, rocks, geysers, and even extreme hot and cold conditions. Microbes are unicellular or multicellular organisms and belong to three domains i.e. archaea, bacteria, and eukarya. These tiny creatures are truly a gift from God as they play several roles for the environment and every creature of the earth such as humans, plants, and animals, without (gnotobiotic condition) which quality and quantity of life will drastically reduce. Microbes maintain the biogeological cycles in the environment and on the other hand they maintain the soil fertility. In plants, beneficial microbes help in plant growth promotion as well as protecting them from pathogens and fulfilling nutritional requirements, whereas in humans and animals, they maintain cognitive functions. The importance and their role played in nature the attracted the attention of scientists over the past many decades. Microorganisms have been studied via culturable and unculturable (metagenomics) techniques.
Analysis and Design of Configurable Rectifier With Compensated Near-Zero Impedance Angle for Megahertz Wireless Power Transfer

Adapting to wide load range variations is always one of the main goals pursued by megahertz (MHz) wireless power transfer (WPT) systems. For this, the nonlinear phenomenon of the rectifier has become a problem that must be solved. Compared with the method of optimizing the efficiency around the maximum power point in the traditional design, this article proposes a global load optimization method. Meanwhile, a novel configurable compensated near-zero impedance angle rectifier (NIAR) is proposed to take full advantage of the global optimization method. The NIAR not only realizes the compression of a wide range of impedance angles, but also solves the classic problems of Class E rectifiers, such as large stress, voltage asymmetry, and low real part of input impedance. The configurable design allows the system to adjust the rectifier unit according to the output index, thereby fully improving the coil efficiency, and providing a solution for the application of high-voltage and high-power MHz WPT systems in the future. To verify the effectiveness of the proposed NIAR and design method, a 60-W prototype was built and a traditional full-wave rectifier was used for comparison. The results show that the proposed NIAR system exhibits better characteristics in terms of system efficiency, voltage stress, and symmetry.