Miracle-dz/UniFAR-FTUs huggingface dataset:
Research on medical image segmentation algorithm based on deep learning

For the diagnosis of cancer and tumors, medical pathological image analysis is critical. Whereas, due to the diversity and complexity of pathological data, the segmentation task is faced with challenges such as blurred edges, less training data, difficulty in feature extraction and case segmentation. The advancement of deep learning technologies has resulted in breakthrough achievements in medical image analysis by its powerful feature learning, flexible design, and other characteristics, and it has widely applied. In recent years, many scholars have improved the classic segmentation method. By combining various segmentation methods, segmentation efficiency has effectively improved, and the improved algorithm makes up for the defects of the original segmentation method. In this review, we evaluated and examined the recent research accomplishments in medical picture segmentation using various deep learning approaches, as well as the future research directions for medical image segmentation using deep learning.
Motion Control of a Gymnastics Robot Using Virtual Holonomic Constraints

Motion Control of a Gymnastics Robot Using Virtual Holonomic Constraints Xingbo Wang Master of Applied Science Graduate Department of Electrical and Computer Engineering University of Toronto 2016 In this thesis the motion control problem of a gymnastics robot performing a bar routine is analysed, and a comprehensive solution is developed using the framework of virtual holonomic constraints. The routine is a combination of swinging manoeuvres on the bar and a back-flipping dismount in the air. Virtual holonomic constraints are used extensively to parametrize the motions, for which stabilizing controllers are developed. Using tools such as high-gain observers, Poincaré analysis, and linearization about a trajectory, the virtual constraints are dynamically reshaped so as to meet the control objectives for each motion. A physical gymnastics robot was built in the lab, and experiments were conducted to verify the theoretical predictions. Results show that the solutions developed were robust to real-world imperfections.
Model‐based periodic event‐triggered stabilization for continuous‐time stochastic nonlinear systems

In this paper, we investigate a model‐based periodic event‐triggered control framework for continuous‐time stochastic nonlinear systems. In this framework, an auxiliary approximate discrete‐time model of stochastic nonlinear systems is constructed in the controller module, which is utilized not only to design a discrete‐time controller but also as a state predictor within trigger intervals. This discrete controller design approach, the strategy of state prediction, and the periodic detection strategy for the trigger rule not only provide a manner of more direct and easier implementation on the digital platform but also effectively reduce the communication load while a satisfactory control performance is maintained. Additionally, the mean‐square exponentially stabilization for continuous‐time stochastic nonlinear systems is achieved, in which a guideline for determining the maximum admissible sampling period is provided and the periodic event trigger rule is designed. The final numerical simulation also supports the effectiveness of our proposed framework.
Appendiceal Orifice Inflammation Is Associated with Lower Rate of Complete Endoscopic Remission in Patients with Ulcerative Colitis

Appendiceal orifice inflammation (AOI) is commonly considered a skip lesion in ulcerative colitis (UC). However, the clinical significance of AOI in UC patients remains controversial. This study aimed to evaluate the clinical feature and long-term outcomes of AOI by comparing UC patients with and without AOI. This study was conducted as a retrospective design of patients who were newly diagnosed or referred within 3 months after diagnosis at Seoul St. Mary’s Hospital from 1 January 2001 to 31 December 2020. All patients underwent index and follow-up colonoscopies. The long-term outcomes involved achieving complete endoscopic remission (ER), use of biologics, hospitalization, and proximal disease extension. Complete ER was defined as Mayo endoscopic subscore 0. In total, 318 UC patients were included, of which 140 had AOI. The baseline characteristics were not significantly different between AOI and non-AOI groups. The cumulative risk of complete ER was a significant difference between AOI and non-AOI groups (p = 0.041). The other cumulative risks of disease outcomes were not significantly different between AOI and non-AOI groups (use of biologics, p = 0.542; hospitalization, p = 0.795; proximal disease extension, p = 0.403). The multivariate Cox regression analysis also revealed that AOI was the significant factor of complete ER (hazard ratio, 0.656; 95% confidence interval, 0.462–0.932; p = 0.019) in UC patients. AOI shows a significant association with lower rate of complete ER in UC patients. Therefore, a meticulous treatment strategy may be recommended to achieve complete ER in UC patients with AOI.
A Review on Access to Agriculture Finance by Farmers and its Impact on their Income

Purpose: Agricultural financing is a critical component of all agricultural development operations aimed at improving the productivity. Farmers must have access to sufficient and timely financing for irrigation, farm mechanisation, and land expansion. The main goal of the study is to identify and explore the factors affecting agriculture finance, understand the challenges faced by the farmers, to compare the growth of farmer’s income before and after availing finance support and the strategies required to improve the agriculture credit to farmers. Design/Methodology/Approach: The study is based on secondary data gathered from several publications, websites, and other pertinent substance from NABARD and RBI annual reports. Findings: The study revealed that smallholder systems, policies, and investments are meant to improve infrastructure, boosting efficiency to expand and finance services, and increasing labour availability or automation; formal financial outlets have improved in region regions; financial institution violations are regulated by regulatory frameworks, such as charging exorbitantly high interest rates or taking excessive risks with people’s savings or investors’ assets; and financial institution violations are controlled by regulatory frameworks, such as charging exorbitantly high interest rates or taking unnecessary. Originality/Value: This study is infrequent in that it endeavours to trace the access of agricultural finance by farmers, as well as its impression on farmer’s income level varying to numerous agricultural strategies that have been enacted as a result of agricultural finance. Paper type: Review Paper
Determinants of multidimensional rural poverty in Burji and Konso area, Southern Ethiopia

Abstract This study was conducted in Burji and Konso area, Southern Ethiopia, specifically to measure the status of multidimensional poverty of rural households and to find its determinants. To address these objectives, 368 households were selected using simple random sampling techniques. The data were collected from primary and secondary sources. The interview schedule was used to collect primary data. Secondary data were collected from books, journals from the internet, unpublished researches, and different official reports. Both descriptive and inferential statistics were implemented. Alkire & Foster’s methodology with modified four dimensions and 14 indicators was used to analyze the multidimensional rural poverty index and a binary logistic regression model was employed to detect its determinants at the household level. Accordingly, the incidence of 76.6%, the intensity of 54.7%, and the multidimensional poverty index (MPI) of 0.419 were obtained in the study area. The value of multidimensional poverty varies across poverty cutoffs suggesting that the Adjusted Headcount Ratio (MPI) value is highly sensitive to the choice of multidimensional poverty cutoff. The binary logistic regression model output in marginal effects indicated as the education level of the household head was significant at a 1% significant level. The other variables livestock, farm size, and distance to the market were significant at a 5% significant level. Hence, expansion of non-formal education, expansion of off-farm and non-farm job opportunities, intensification and diversification of agricultural activities, provision and strengthening livestock extension of poultries, and small ruminants improved breeds were recommended to be practical by Woreda to regional level officials.
Deep Learning Approaches for Air-Writing Using Single UWB Radar

Air-writing is an emerging and promising method for contactless human-machine interaction. This paper proposes a novel air-writing framework based on a single ultra wide-band radar (UWB). The framework employs a simple data capture and a processing pipeline facilitated by deep learning approaches, where a number of data representations and models are explored. Two different data representations are proposed, two-dimensional and three-dimensional range-Doppler spectrogram. The deep learning approaches include, fully connected neural networks, convolutional neural networks, three-dimensional convolutional neural networks, and hybrid two-dimensional and three-dimensional convolutional neural networks long short-term memory recurrent neural networks. A dataset of 1,800 samples containing 10 air-written numbers is collected to train, validate, and test the performance of the proposed methods. It is shown that hybrid convolutional neural networks long short-term memory recurrent neural networks architectures can effectively predict air-written numbers with an accuracy of 98.5%. The experimental results suggest the efficacy of the proposed approaches for practical and convenient air-writing applications.
Population and economic growth in developed countries

ABSTRACT The relationship between population growth and economic growth is examined. Evidence is provided on the direction of causality between population and GDP in five industrialized countries (US, UK, Germany, France, and Italy) for the periods 1820–1938 and 1950–2016. Using Toda-Yamamoto Granger causality tests and Sims causality test it was found that the direction of causality during the former period was from Population to GDP or bidirectional while for the latter period, it was from GDP to population. It is also shown that during the second period per capita GDP was almost double relative to the first period. We argue that the difference may be partly explained by the direction of causality between the two variables. In the 1820–1938 period, the direction of causality is probably due to the large family model that prevailed in that period that led to rapid population growth. For the 1950–2016 period it is probably the rapid economic growth that followed the Second World War and motivated large migration flows to the developed countries we examined.
Relationship difficulties and “technoference” during the COVID-19 pandemic

The COVID-19 pandemic has touched many aspects of people’s lives around the world, including their romantic relationships. While media outlets have reported that the pandemic is difficult for couples, empirical evidence is needed to test these claims and understand why this may be. In two highly powered studies (N = 3271) using repeated measure and longitudinal approaches, we found that people who experienced COVID-19 related challenges (i.e., lockdown, reduced face-to-face interactions, boredom, or worry) also reported greater self and partner phone use (Study 1) and time spent on social media (Study 2), and subsequently experienced more conflict and less satisfaction in their romantic relationship. The findings provide insight into the struggles people faced in their relationships during the pandemic and suggest that the increase in screen time – a rising phenomenon due to the migration of many parts of life online – may be a challenge for couples.
CRITICAL FRAMEWORK-CONDITIONS FOR STRATEGIC DEVELOPMENT PROGRAMMING

Local development is multifunctional and complex process which incorporates different aspects like creation of planning and management methodology mainly through construction of relevant data base, key performance indicators, diagnostics reports, strategic action plans, generation of project ideas and proposals as well local development program implementation. It also incorporates a process of monitoring and evaluation of local development initiatives as well as connectivity with overall regional and macro-economic policies. So in the paper are specifically analyzed and discussed critical framework-conditions for strategic development programming which has been appeared in West Balkan Countries, Republic of Croatia and Serbia during the regional and local development projects implementation. The main critical framework conditions regards to Impediments on a Local level connected with different structures which led to different experiences, successes and problems; Accuracy and relevance of data and information; Institutional competence; Consideration of horizontal and vertical relations of local community which neglect their required active role in the development process; Financial restrictions as a considerable bottleneck for successful development planning upon unstable resource flow; Political culture norms and values; and The role of external experts and improvement of the above mentioned aspects which will enhance the situation of development planning at the local level in a sustainable manner. So any interventions must consider these interdependencies and the technical assistance in the field of local or regional development based on long term involvement. It is also concluded that the success of development efforts of the subordinated administrative levels depends to a high degree on adequate framework-conditions, which have to be formed and fostered at the superior level.
Comparison of Open and Robot-Assisted Kidney Transplantation in terms of Perioperative and Postoperative Outcomes

Background The gold standard treatment method for end-stage renal disease (ESRD) is renal transplantation (RT). RT can be done with open or minimally invasive surgical methods. We aimed to compare the outcomes between patients who underwent robot-assisted renal transplantation (RART) and open renal transplantation (ORT). Methods Data of the patients who underwent ORT or RART in two institutions between June 2015 and February 2020 were retrospectively reviewed. Patients who underwent live donor RT were included, and all donor nephrectomy procedures were performed by the laparoscopic technique. Demographic data, ischemia times, anastomosis times, operation times, and postoperative complications were recorded. Results 98 patients were included in the ORT group, while 91 patients were included in the RART group. There was a significant difference between the two groups regarding mean patient age. While total ischemia time was 86.9 ± 7 minutes in the RART group, it was calculated as 71.2 ± 3.3 minutes in the ORT group, with a significant difference. The anastomosis time was significantly shorter in the ORT group than in the RART group. The incision length and duration of hospital stay were significantly shorter, visual analogue scores were significantly lower, and estimated blood loss was less in the RART group than in the ORT group. Conclusion Both ORT and RART are effective and safe methods for treating ESRD. According to our study, RART is associated with relatively longer ischemia times but lower complication rates and higher patient comfort.
The Impact of Biofuel Intensification on Integrated Climate-Land-Energy-Water System

Producing biodiesel using a mixture of palm oil is one of the main policies today. This paper studied the interactions among climate, land, energy, and water in a model to address national biofuel intensification policies and identified biofuels’ role in fulfilling energy needs, the trade balance, and reducing greenhouse gas emissions. The integrated climate land energy system (CLEWs) model was employed here. The model simulated the implementation of B30 in 2020 (B30/20), B40/25, and B50/30. The results showed that the implementation of the B30/20, B40/25, and B50/30 scenarios requires 15.30, 20.20, and 25.10 million tons of Crude Palm Oil (CPO), respectively. In terms of land, implementing the B30/20, B40/25, and B50/30 scenarios needs an additional 8.36, 69.33, and 80.38 thousand km2 of oil palm plantations, respectively 2030. In terms of emission, implementing the B40/25 and B50/30 policies can reduce 160 MTon and 320 MTon CO2-eq, respectively by 2030. There is no irrigation system needed in oil palm plantations. The paper recommended that the biofuel incentives or need price mechanism formulation and land allocation policies by using marginal/critical land for new oil palm plantations. The policy should be used to improve the yield or crop productivity of palm oil plants.
IMPLEMENTASI QRCODE PADA BERKAS KELULUSAN MAHASISWA BERBASIS PDF WEB

Pemalsuan ijazah dan transkrip hasil studi saat ini sedang marak terjadi baik ditingkat sekolah menengah, maupun perguruan tinggi saat ini marak sekali terjadi. Modus yang dilakukan pun sangat bervariasi, mulai menggunakan staff/orang dalam di perguruan tinggi, hingga menggunakan nama universitas terkenal di luar negeri secara illegal. Teknologi berbasis web dan QR-Code mampu menjebatani dalam proses pengecekan keaslian ijazah maupun transkrip dengan cara menempelkan QR-code pada ijazah dan transkrip. Sehingga semua pihak yang menggunakan syarat ijazah dan transkrip sebagai syarat tertentu dapat melakukan pengecekan secara online menggunakan Handphone/smartphone yang mendukung pembacaan QR-code.
An unusual cause of a haemothorax following pacemaker implantation: A case report

Abstract Background Haemothoraces are a reported but extremely rare complication of pacemaker implantation. Haemothoraces can be a consequence of lead perforation through the right ventricle (RV) and pericardium into the pleural space, direct lung or vascular injury during access. Case summary A 72-year-old woman presented 24 h after a pacemaker implantation with chest pain and shortness of breath. Computed tomography of the chest confirmed perforation of the RV lead into the left pleural cavity with a large left sided haemothorax. Following percutaneous drainage of the left sided haemothorax, the patient became haemodynamically unstable necessitating emergent sternotomy. During surgery, the extra-cardiac portion of the pacing lead was cut, the RV repaired and a large haematoma evacuated from the left pleural space. Despite this, the patient remained hypotensive, and further exploration showed a bleeding intercostal artery that had been lacerated by the pacing lead. This was treated by electrocautery, and the patient’s haemodynamic status improved. The RV lead remnant was removed transvenously via the subclavian vein, and the patient was left with a single chamber atrial pacemaker. Discussion Prompt recognition of RV lead perforation and its associated sequalae, often utilising multi-modality imaging, is vital to enable transfer to a centre with cardiac surgical expertise. In this case, the perforating RV lead lacerated an intercostal artery, and this was only identified at the time of surgery. In order to minimize the risk of perforation, multiple fluoroscopic views should be used, and care should be taken during helix deployment.
Numerical modelling and analysis of a room temperature magnetic refrigeration system

This thesis presents a two-dimensional mathematical model of an Active Magnetic Regenerator (AMR) system which is used for magnetic refrigeration at room temperature. The purpose of the model is to simulate a laboratory-scale AMR constructed at Risø National Laboratory. The AMR model geometry comprises a regenerator made of parallel plates, which are separated by channels of a heat transfer fluid. The time-dependent model solves the momentum and continuity equations of the flow of the heat transfer fluid and the coupled energy equations of the heat transfer in the regenerator and the fluid. The AMR performs a cyclic process, and to simulate the AMR refrigeration cycle the model starts from an initial temperature distribution in the regenerator and fluid channel and takes time steps forward in time until the cyclical steady-state is obtained. The model can therefore be used to study both transient and steady-state phenomena. The AMR performance can be evaluated in terms of the no-load temperature span as well as the refrigeration capacity and the COP. The AMR model was verified extensively and it was concluded that the model has energy conservation and that the solution is independent of the chosen grid and time step. Initial results from the model showed significant temperature differences in both the regenerator and the fluid channel during the AMR cycle. This justifies the use of two-dimensional methods when an AMR with a parallel-plate regenerator is modelled. The model is flexible and was used to perform several parametric studies of the AMR performance for different design choices and operating conditions. The results of these studies are presented and the implications for optimal AMR operation are discussed. Finally, the AMR model was validated by comparing the model result to measurements from the experimental AMR constructed by Risø. The validation shows good agreement between the model and the experiments and it is possible to predict both the trends as well as the temperature span of the experimental AMR. In addition, the model can estimate the optimal operating conditions with good accuracy. The ability to provide good results of both the behavior and the performance of the experimental AMR shows that the developed model is a useful tool, which may be used for analysis, design and optimization of the laboratory AMR.
CONFIDENTIALITY-MAINTAINING PUBLIC ASSESSING FOR RESTORING-CODE-BASED CLOUD STORAGE

Several techniques that deal with the sturdiness of outsourced data missing of local copy were recommended in many models up to now. Fliers and card printing of remote trying to find regenerating-coded information provide private auditing, necessitates data keepers to constantly stay web mange auditing. We introduce a apparent auditing method of regeneration-code-basis cloud storage. For solving regeneration impracticality of ineffective authenticators in inadequate data proprietors, we initiate a proxy, which regenerate authenticators, into established public auditing system representation. As opposed to direct improvement in fliers and card printing of public auditing towards multi-server setting, we advise novel authenticator, that's suitable for regenerating codes that's produced by means of several keys and they're regenerated by means of partial keys hence our method can totally make data owner’s burden free.
Multi-view low-rank sparse subspace clustering based on adaptive dictionary learning

With the development of science and technology, image processing gradually develops towards higher dimensions. High-dimensional data is usually regarded as approximated by the union of multiple low-dimensional data. That is, the high-dimensional subspace is divided into several low-dimensional subspaces, so as to provide better insights for understanding the underlying structure of the high-dimensional subspace. Most of the existing clustering methods solve the problem of Multi-view subspace clustering by constructing an affinity matrix on each view. This paper proposes a Multi-view low-rank sparse subspace clustering based on adaptive dictionary learning(ADLMLRSSC). In the multi-view low rank sparse representation model, an adaptive dictionary learning strategy using orthogonal constraints is introduced. The dictionary learns adaptively from the original data, which makes the model robust to noise. At the same time, the projection matrix and sparse low rank features are obtained by the optimization method. In theory, low rank and sparse constraints can consider both the global and local structure of the matrix.