Miracle-dz/UniFAR-FTUs huggingface dataset:
Can sural nerve injury be avoided in the sinus tarsi approach for calcaneal fracture?

Abstract There is no consensus regarding the references to determine the exact location of the skin incision to minimize iatrogenic sural nerve injury in the sinus tarsi approach for calcaneal fracture. The purpose of this cadaveric study was to describe the anatomical course of the sural nerve in relation to easily identifiable landmarks during the sinus tarsi approach and to provide a more practical reference for surgeons to avoid sural nerve injury. Twenty-four foot and ankle specimens were dissected. The bony landmarks used in the following reference points were the tip of the lateral malleolus (point A), lateral border of the Achilles tendon on the collinear line with point A (point B), posteroinferior apex of the calcaneus (point C), inferior margin of the calcaneus on the plumb line through point A (point D), and tip of the fifth metatarsal base (point E). After careful dissection, the distances of the sural nerve to points A and B in the horizontal direction (lines D1 and D2), points A and C in the diagonal direction (lines D3 and D4), points A and D in the vertical direction (lines D5 and D6), and points A and E in the diagonal direction (lines D7 and D8) were measured. The median ratio of D1 to D1+D2, D3 to D3+D4, D5 to D5+D6, and D7 to D7+D8 were 0.37 (range, 0.26–0.50), 0.23 (range, 016–0.33), 0.35 (range, 0.25–0.45), and 0.32 (range, 0.20–0.45), respectively. The distance ratios from this study can be helpful to avoid sural nerve injury during the sinus tarsi approach for calcaneal fractures. Established standard incision may have to be modified to minimize sural nerve injury.
Tebu adalah salah satu komoditas perkebunan penting yang dikembangkan secara nasional. Tanaman ini dimanfaatkan sebagai komponen alami pada berbagai industri. Peningkatan kebutuhan tebu nasional tidak diikuti dengan peningkatan produktivitas tebu. Pemanfaatan lahan marginal adalah salah satu upaya y

Tebu adalah salah satu komoditas perkebunan penting yang dikembangkan secara nasional. Tanaman ini dimanfaatkan sebagai komponen alami pada berbagai industri. Peningkatan kebutuhan tebu nasional tidak diikuti dengan peningkatan produktivitas tebu. Pemanfaatan lahan marginal adalah salah satu upaya yang potensial untuk meningkatkan produksi nasional tebu. Sebagian besar lahan daratan Indonesia termasuk lahan masam dengan tingkat kemasaman yang tinggi dan konsentrasi aluminium (Al) yang mencapai tingkat toksisitas. Genotipe tebu baru yang toleran terhadap lahan masam dapat diperoleh melalui seleksi in vitro terhadap massa sel embriogenik dalam media seleksi yang mengandung Al. Penelitian ini bertujuan untuk mengetahui respon kalus dari beberapa varietas tebu pada kondisi tercekam Al. Varietas yang digunakan dalam kegiatan ini adalah PS864 dan BL. Massa sel embriogenik diseleksi dalam media yang mengandung Al3.6H2O (0, 100, 200, 300, 400, dan 500 mg/l). Hasil pengujian kalus tebu pada kondisi tercekam Al terlihat bahwa varietas BL lebih resisten dari PS864. Respon kalus terhadap Al memperlihatkan perubahan terhadap morfologi kalus yaitu perubahan warna pada kalus yang menjadi coklat atau hitam dan akhirnya mengalami kematian. Respon kalus terhadap cekaman Al juga berpengaruh terhadap tinggi tunas (tertinggi 5,68 cm) dihasilkan dari varietas PS864 dan jumlah tunas terbanyak yaitu 6,11 dihasilkan dari varietas BL.
COMPARISON OF THREE DIFFERENT TREATMENT METHODS ON PAIN AND DISABILITY OF PEOPLE WITH NON-SPECIFIC CHRONIC LOW BACK PAIN

Numerous recovery strategies have been used in an attempt to minimize the symptoms of low back pain (LBP). However, scientific evidence to support the effects of a Combination Treatment on low back pain is lacking. The purpose of the present study was to compare the effectiveness of a combined - physical exercise program versus routine exercise and posture education on pain and disability of people with nonspecific chronic low back pain. The study was designed as a clinical and pseudo-experimental trial set at University laboratory. The participant s included a population of 33 men gaining from 18 to 45 years old with chronic low back pain. The interventions in this study were Routine therapeutic protocol, a combined - therapeutic protocol (Therapeutic Aquatic Exercise and foam roller and Swiss-ball exercises plus massage), posture education (back school), all delivered by experienced Physical therapists, thrice a week for 6 weeks. Measurements: Sorensen Test, Trunk flexors endurance test, Side bridge endurance test, Modified schober test, McGill Pain Questionnaire (MPQ), Roland-Morris Disability Questionnaire (RMDQ). There were differences between the groups at 6 weeks for pain measurements (MPQ), disability scores (RMDQ). A combined - physical exercise program is more effective than general exercise for decreasing pain and disability, eventually, improving quality of life and function in a population suffering from chronic low back pain.
Activity recognition evaluation via machine learning

With the proliferation of relatively cheap Internet of Things (IoT) devices, smart environments have been highlighted as an example of how the IoT can make our lives easier. Each of these ‘things’ produces data which can work in unison to react to its users. Machine learning makes use of this data to make inferences about our habits and activities, such as our buying preferences or likely commute destinations. However, this level of human inclusion within the IoT relies on indirect inferences from the usage of these devices or services. Activity recognition is already a widely researched area and could provide a more direct way of including humans within this system. This research explores the feasibility of using a cost effective, unobtrusive, single modality ground-based sensor matrix to track subtle pressure changes to predict user activity, in an effort to assess its ability to act as an intermediary interface between humans and digital systems such as the IoT.
Altered expression of microRNA-30a-3p in papillary thyroid cancer and its association with clinicopathological characteristics

Paper description: Identification of novel molecular biomarkers can aid in stratification of patients with papillary thyroid cancer (PTC) into low- and high-risk prognostic groups. A growing body of evidence suggests a role for microRNA-30a-3p in aggressiveness and progression of various types of cancer. We show that miR-30a-3p expression levels were deregulated in PTC compared to non-tumor thyroid tissues. Decreased expression was associated with advanced stage, multifocality and capsular invasion. This is one of few studies of microRNA-30a-3p expression in PTC, indicating its potential involvement in the development and/or progression of this type of cancer. Abstract: A growing number of studies suggest a tumor suppressive role and potential prognostic significance of miR-30a-3p in different types of cancer. However, relatively few studies have focused on this microRNA in neoplastic thyroid lesions, including papillary thyroid cancer (PTC). The aim of our study was to shed more light on the potential involvement and clinical relevance of miR-30a-3p in this type of cancer. We examined the expression levels of this microRNA in 42 pairs of PTCs and matched non-tumor thyroid tissues using quantitative RT-PCR. We analyzed their association with clinical and histopathological parameters. The results revealed that miR-30a-3p was significantly downregulated in the majority of PTC tissues compared to corresponding non-tumor tissues. Moreover, decreased expression of miR-30a-3p was associated with advanced clinical stage, presence of multiple tumor foci and capsular invasion, suggesting a role in aggressive disease. Although the role of this microRNA and its prognostic utility remain to be elucidated, the presented data suggest that downregulated expression of miR-30a-3p indicates poorer prognosis in PTC patients, warranting further investigations. https://doi.org/10.2298/ABS191004063T Received: October 4, 2019; Revised: October 14, 2019; Accepted: October 15, 2019; Published online: October 25, 2019 How to cite this article: Todorovic L, Mandusic V, Vucetic Tadic B, Živaljevic V, Paunovic I, Stanojevic B.Altered expression of microRNA-30a-3p in papillary thyroid cancer and its association with clinicopathological characteristics. Arch Biol Sci. 2020;72(1):31-6.
Urinary NAG as a Biomarker of AKI in Patients with Hepatorenal Syndrome

Early detection of acute kidney injury in patients with decompensated liver cirrhosis by urinary N-acetyl-b-D glucosaminidase (NAG). Background: Renal failure is a challenging complication of liver cirrhosis primarily related to reduction in systemic vascular resistance due to splanchnic vasodilatation triggered by portal hypertension also in some patients, with cirrhosis, intrinsic renal diseases may be present that are related not to alternations in systemic hemodynamics but rather to etiological factors underlying the liver disease such as glomerulonephritis associated with hepatitis B or hepatitis C infection. Methods: Forty patients with advanced decompensated liver cirrhosis, with different ages and developed acute kidney injury (AKI) due to variable precipitating factors such as tapping of large volume of ascites in 25 patients, spontaneous bacterial peritonitis in 9 patients, haematmesis in 6 patients and ten age and sex matched normal persons were screened urinary NAG level 12 & 48 hours after admission. Results: The study group included 28 males and 12 females (M:F = 2.33:1) and their ages ranged from 42 to 67 (mean ± SD = 59 ± 5.3 years). In these patients the first urine sample which taken 12 hours after admission for assessment of NAG level ranged from 40 to 200 IU\L (mean ± SD = 88.7 ± 39.9) and second urinary NAG sample which taken 48 hours after admission ranged from 41 to 198 IU\L (mean ± SD = 100 ± 44.1). Comparison between laboratory data of study group (N= 40) and control group (N=10) revealed significant differences between 2 groups in laboratory data especially regarding mean urinary NAG levels 12 & 48 hours after admission with statistically significant P value = 0.0001. Comparison between Urinary NAG levels 12 hours (mean ± SD = 88.7 ± 39.9) and 48 hours (mean ± SD = 100 ± 44.1) for patients of study group revealed statistically significant P value = 0.0001. We conclude that Urinary NAG is a reliable biomarker for detection of AKI in patients with chronic liver disease and that it allows early detection of AKI before serum urea and creatinine.
Application of Cluster Analysis with Unsupervised Learning to Dockless Shared Bicycle Flow Control and Dispatching Authors:

Introduction: The promotion of shared bicycles seeks to resolve the problem of short-distance urban transportation, and shared bicycles are an important means of contemporary green transportation [2]. However, after dockless shared bicycles are introduced on a large scale in the city, supply and demand problems involving different areas often emerge. This study applied cluster analysis with unsupervised learning to shared bicycle flow control and dispatching, and employed artificial intelligence to extract real, fullscale transportation rules from open data. First, this study proposes a model of shared bicycle control system and an incentive mechanism for reverse flow of bicycles based on threshold values. Then, we use the kernel density spatial clustering method to perform partitioning, grading, and incentives of checkout and check-in points’ density in the area, furthermore, adopt the DBSCAN clustering method to establish dispersal and dispatching strategies. This study use Shanghai Open Data in modeling, verification, and used Rstudio software to produce visualized interactive graphics for demonstration.
THE WIENER MEASURE AND DONSKER’S INVARIANCE PRINCIPLE

We give the construction of the Wiener measure (Brownian motion) and prove Donsker’s invariance principle, which shows that a simple random walk converges to a Wiener process as time and space intervals shrink. To build up the mechanisms for this construction and proof, we first discuss the weak convergence and tightness of measures, both on a general metric space and on C[0, 1], the space of continuous real functions on the closed unit interval. Then we prove the central limit theorem. Finally, we define the Wiener process and discuss a few of its basic properties.
Contributing Factors That’s Effect to Istishna Mode of Financing Performance at Sharia Banking in Indonesia and Malaysia

The development of Islamic banks along with sharia units from year to year reflects increase the public confidence to istishna mode of financing of sharia bank. This study aimed to determine the influence of deposits, equity, non-performing financing, and growth non-performing financing to istishna financing both on partial and simultaneous measurements. The sample selected in this study was sharia commercial banks operating in Indonesia and Malaysia. This research used purposive sampling method, the sampling research was includes BRI Syariah, Maybank, Mandiri Syariah, Muamalat, Malaysia Affin Islamic Bank Berhad. The analytical method used regression analysis of the balanced panel. The f test results showed that the variable of deposits, equity, non performing financing and growth non performing financing simultaneous had has positif effect on Istishna financing. The t test results showed deposit variable, equity, and growth non performing financing partially had has positif effect on the Istishna financing. The only non performing financing has a significant negative relationship to the variable of financing Istishna. While The coefficient of determination showed all independent variables contributed predominant percentage portion to the dependent variable. The remaining minor percentage portion might be influenced by other variables, which did not exists in this research such as Capital Adequacy Ratio, Loan Deposit Ratio, and the level of foreign currencies reserve owned by the banks etc.
Graph neural network for situation recognition

Understanding images beyond salient actions involves reasoning about scene context, objects, and the roles they play in the captured event. Situation recognition has recently been introduced as the task of jointly reasoning about the verbs (actions) and a set of semantic-role and entity (noun) pairs in the form of action frames. Labeling an image with an action frame requires an assignment of values (nouns) to the roles based on the observed image content. Among the inherent challenges are the rich conditional structured dependencies between the output role assignments and the overall semantic sparsity. In this work, we propose a novel mixture-kernel attention graph neural network (GNN) architecture designed to address these challenges. Our GNN enables dynamic graph structure during training and inference, through the use of a graph attention mechanism, and context-aware interactions between role pairs. It also alleviates semantic sparsity by representing graph kernels using a convex combination of learned basis. We illustrate the efficacy of our model and design choices by conducting experiments on imSitu benchmark dataset, with accuracy improvements of up to 10% over state-of-the-art.
Review of Data Mining Applications

This paper focuses on real life applications, where data mining techniques are used. From the last few decades data mining has emerged as a powerful technique to manage data. In every field data is available in huge amount. It is necessary to handle this abundant data so that it can be easily retrieved and the technique used to analyze and manage this data is called as data mining. The purpose of this paper is to survey the applicability of data mining in different fields. The limit of our discussion is to the areas where data mining is used to a high extent. Such areas include education system, agriculture, e-commerce, healthcare, business, and telecommunication.
Formulation of A Bulk Boundary Layer Model With Partial Mixing and Partial Cloudiness

The classical cloud-topped mixed-layer mcxlel is generalized to allow for arbitrary fractional cloudiness and incomplete mixing. The boundary-layer depth and turbulence kinetic energy (TKE) are prognostically determined. The large turbulent eddies that contain most of the TKE and are primarily responsible for the fluxes are modeled as convective circulations, with ascending and descending branches. By assuming that the ventilation and entrainment layers at the lower and upper edges of the PBL are dominated by small-scale turbulence in quasicquilibrium, boundary conditions are developed for the rising and sinking branches of the convective circulations, and also for the scalar variances associated with the convective circulations. The convective mass flux and the fractional area covered by updrafts arc diagnosed by the model. Fractional cloudiness occurs when the ascending branches are saturated and the descending branches are not. We use a modified bulk formula in which the square root of the TKE takes the place of the wind speed. The advantages of this approach are discussed. The entrainment rate is also assumed to be proportional to the square root of the TKE; the proportionality factor depends on the inversion Richardson number, and also on an additional parameter that represents the effects of evaporative cooling when clouds are present The ventilation mass flux is similarly parameterized. Instead of using a conventional bulk formula in which the wind speed is multiplied by a transfer coefficient, we use a modified bulk formula in which the square root of the TKE takes the place of the wind speed. The advantages of this approach are discussed. Large-eddy simulations arc used to validate several aspects of the model's formulation. For the special case of a well-mixed layer, the model predicts that the fractional area covered by rising motion is near 1/2, and that dissipation in the interior of the layer is weak. When the dissipation is weak and the fractional area covered by rising motion is small, the model gives the "compensating subsidence -detrainment" relationship that has become familiar in cumulus parameterization theories. When the dissipation is strong and the fractional area covered by rising motion is near tn. , the model gives downgradient diffusion. For the shallow cumulus regime, the model predicts that the fractional area covered by rising motion is smaller for the case of large-scale rising motion than for that of large-scale sinking motion. A number of idealized dry cases are simulated to illustrate the model's ability to predict the development and evolution of partially mixed states. More extensive results, including both overcast and partly cloudy cases, are presented in a companion paper.
System identification and a linear time invariant-model of an insect-sized flapping-wing micro air vehicle

Flapping-wing robots typically include numerous nonlinear elements, such as nonlinear geometric and aerodynamic components. For an insect-sized flapping-wing micro air vehicle (FWMAV), we show that a linearized model is sufficient to predict system behavior with reasonable accuracy over a large operating range, not just locally around the linearization state. The theoretical model is verified against an identified model from a prototype robotic fly and implications for vehicle design are discussed.
Özet—Günümüz teknolojisinde kullanılan akıllı telefonlar

Özet—Günümüz teknolojisinde kullanılan akıllı telefonlar mobil işletim sistemlerine sahiptir. Bu mobil işletim sistemleri her kullanıcı ihtiyacına göre farklılık göstermektedir. Açık kaynak kodlu ve Linux tabanlı bir mobil işletim sistemi olan Android'in yapılan çeşitli araştırmalar sonucunda en popüler işletim sistemi olduğu görülmüştür [1]. Android'in popüler olması ve açık kaynak kod yapısı, kötücül saldırı tiplerinin ve kötü amaçlı saldırganların hedefi olmasına sebep olmuştur. Bu çalışmamızda, mobil cihazlarda zararlı yazılım tespiti yapan statik analiz yöntemlerinden bahsedilmiş ve bu yöntemlerin özellikleri karşılaştırılmıştır.
Measuring Sovereign Risk: Are CDS Spreads Better than Credit Ratings?

By exploiting the lead-lag structure between sovereigndebt ratings andCDS,wefind that a country’s CDS spread is an explanatory variable for its sovereign debt rating. At the annual level, CDS spreads are a predictive variable for both positive and negative rating changes. At themonthly level, the CDS spreads can only predict the negative rating changes. Wefind that the negative rating changes can be predicted up to 7months in advance using the one-month logCDS spread difference. Additionally, a cumulative CDS spread change that is greater than 40% in a seven-month period triggers negative rating events.
Constraining Cooperation: Military Relations and Government Repression

Sometimes states repress political campaigns harshly, and sometimes they do not. Why? I argue that military cooperation with liberal democracies constrains the state from using severe forms of repression against opposition campaigns. Liberal democracies face costs for human rights violations by their friends, and are likely to coerce the military from repressive actions. Such interconnectedness also socializes the military with democratic militaries that have strong norms against the use of widespread and excessive repression. However, the military is not the only repressing agency, and therefore this constraint does not act to prevent repression but rather to limit its severity. This theory is tested using the NAVCO data and a new, latent measure of military cooperation. I find that military cooperation with liberal democracies does not prevent the state from repressing opposition movements, but it does limit the severity. This finding provides evidence of one benefit to expanding multinational security cooperation initiatives involving liberal democracies.
A Sentiment Analysis Method to Better Utilize User Profile and Product Information

Sentiment analysis which aims to predict users’ opinions is a huge need for many industrial services. In recent years, many methods based on neural network achieve great performance on sentiment analysis such as Tang et al. (2014); Socher et al. (2013); Mikolov et al. (2013b). However, most of existing methods only focus on local documents and do not consider related user profile and product information (Kim, 2014; Yang et al., 2016; Long et al., 2017). Even some works attempt to combine those background information in sentiment analysis, they normally treat user profile and product information as a united entity and ignore that different background information may cause different aspects of influences to users’ sentiments(Tang et al., 2015b; Chen et al., 2016; Dou, 2017). To address these issues, we proposed a new Joint User and Product Memory Network (JUPMN) utilizing user profile and product information in separate ways into sentiment classification. Inspired by the successful utilization of memory network (Weston et al., 2014; Sukhbaatar et al., 2015), our model first creates document representations using hierarchical LSTM model and then feeds the document vectors into new carefully designed user and product memory networks to reflect corresponding features. The evaluation of JUPMN on three benchmark review datasets IMDB, Yelp13 and Yelp14 shows that JUPMN outperforms the state-of-the-art model and further analysis of experimental results is employed.