Miracle-dz/UniFAR-FTUs huggingface dataset:
Loss of c-Cbl expression correlates with de-differentiation status and lymphatic metastasis in gastric cancer

Context: C-Cbl is an important negative regulator of the cell signaling that acts as an adaptor protein and E3 ubiquitin ligase. The role of c-Cbl in development and regulation of human cancer has aroused intensive attention. Aims: In this study, we aimed to assess the correlation between the expression of c-Cbl and clinicopathological parameters and explored the role of c-Cbl in the development and progression of GC. Settings and Design: This is a Pilot study. Methods and Materials: In total, 84 tissue samples including 44 gastric cancers (GC) and 40 matched adjacent normal tissues were collected after surgery. Then tissue microarray (TMA) and immunohistochemistry (IHC) technology were combined to detect the protein expression of c-Cbl. Statistical Analysis Used: Statistical analysis was performed using SPSS 22.0 (IBM Corporation, Armonk, NY, USA). Results: We have studied the correlation between c-Cbl expression and clinicopathological parameters. Our study showed that c-Cbl has a low expression in 61.4% (27/44) of GC tissues, and the incidence of cases was significantly higher than that in adjacent normal tissues (P < 0.0001). In addition, the correlation between c-Cbl expression and gastric carcinoma subtype (P = 0.027), histological type (P = 0.033), Borrmann classification (P = 0.009), histological differentiation (P = 0.0005), lymph node metastasis (P = 0.007), and intravascular tumor thrombus (P = 0.036) has also been revealed. Conclusions: Our results show that c-Cbl is down-regulated in GC tissues compared with normal gastric tissue, which may play an important role in the development and progression of GC.
Self-Organizing in Blockchain Infrastructures: Generativity Through Shifting Objectives and Forking

Given the ubiquity of digital technologies, and increased use of autonomous algorithms, it is likely that many of today’s social and organizational processes will one day include autonomous elements. The Bitcoin blockchain is likely the first case of an increasingly generative and autonomous way of organizing, and the specific properties of blockchain infrastructures— distribution of control, openness to manipulation, and generativity of the underlying source code— make it an ideal case to study patterns of self-organizing. This paper investigates the phenomenon of self-organizing through a study of forking in the Bitcoin blockchain infrastructure between 2010 and 2016. It adds to the emerging body of research on digital infrastructures, and particularly blockchain infrastructures, by conceptualizing forking as a pattern of self-organizing in blockchain infrastructures that specifically involves the underlying infrastructure, the scale of code changes, individual objectives, and collective adoption, whether specific or general. Thus, this paper demonstrates how forking in blockchain infrastructures mediates between divergent organizing objectives and existing capabilities, on the one hand, and generates self-organizing on the other hand. In this paper, we further contextualize our findings in extant work on digital infrastructures, offer a guide for designers of blockchain infrastructures, and propose the concept of “generative mirroring” as a pattern through which blockchain infrastructures and organizing adaptively coevolve.
Emerging Drug Combination Approaches in Melanoma Therapy

The FDA approvals of ipilimumab targeting the cytotoxic T lymphocyte-associated antigen 4 (CTLA-4), pembrolizumab targeting the programmed cell death protein 1 (PD-1), BRAF inhibitors vemurafenib and dabrafenib, and MEK inhibitor trametinib represent significant milestones in more effective treatment of advanced melanoma. However, it is clear that the use of these single-agent therapies have limitation clinically. For example, ipilimumab only showed 4.5% objective response rate when used alone in a Phase II clinical trial [1]. The efficacy of vemurafenib lasts only 6.7 months before the disease relapses especially in patients with metastatic melanoma [2]. Therefore, rational combination approaches are strongly preferred in order to improve the overall patient progression-free survival (PFS), overcome or delay the development of multi-drug resistance and reduce the incidents of side effects [3-6].
Risk of malignancy in Thyroid “Atypia of undetermined significance/Follicular lesion of undetermined significance” and its subcategories – A 5-year experience

Context: Atypia of undetermined significance/Follicular lesion of undetermined significance [AUS/FLUS] is a heterogeneous category with a wide range of risk of malignancy [ROM] reported in the literature. The Bethesda system for reporting thyroid cytopathology [TBSRTC], 2017 has recommended subcategorization of AUS/FLUS. Aims: To evaluate the ROM in thyroid nodules categorized as AUS/FLUS, as well as separate ROM for each of the five subcategories. Settings and Design: Retrospective analytic study. Methods and Materials: A retrospective audit was conducted for all thyroid fine-needle aspiration cytology (FNAC) from January 2013 to December 2017. Slides for cases with follow-up histopathology were reviewed, classified into the five recommended subcategories, and differential ROM was calculated. Statistical Analysis Used: z test for comparison of proportions was done to evaluate the difference in ROM among different subcategories of AUS/FLUS. The P value of less than 0.05 was taken as statistically significant. Results: Total number of thyroid FNACs reported was 1,630, of which 122 were AUS/FLUS (7.5%). Histopathology was available in 49 cases, out of which 18 were malignant (ROM = 36.7%). The risk of malignancy (ROM) for nodules with architectural and cytologic atypia was higher (43.8%) than ROM for nodules with only architectural atypia (16.7%). Conclusions: The sub-classification of AUS/FLUS into subcategories as recommended by TBSRTC, 2017 may better stratify the malignancy risk and guide future management guidelines.
Daily measurement of slow slip from low-frequency earthquakes is consistent with ordinary earthquake scaling

Daily M > 4.5 slow transients on tectonic plate boundaries are similar to fast earthquakes. Slow slip transients on faults can last from seconds to months and stitch together the earthquake cycle. However, no single geophysical instrument is able to observe the full range of slow slip because of bandwidth limitations. Here, we connect seismic and geodetic data from the Mexican subduction zone to explore an instrumental blind spot. We establish a calibration of the daily median amplitude of the seismically recorded low-frequency earthquakes to the daily geodetically recorded moment rate of previously established slow slip events. This calibration allows us to use the precise evolution of low-frequency earthquake activity to quantitatively measure the moment of smaller, subdaily slip events that are unresolvable by geodesy alone. The resulting inferred slow slip moments scale with duration and inter-event time like ordinary earthquakes. These new quantifications help connect slow and fast events in a broad spectrum of transient slip and suggest that slow slip events behave much like ordinary earthquakes.
Global Simulation of Insect Meat Production Under Climate Change

The world’s population could exceed nine billion by 2050, putting future global food security at risk. To fulfill the increased food demand, food production should be increased. However, with limited land use, current livestock production is not sustainable. To tackle this problem, insect meat can be used as an alternative to conventional livestock. With its high nutritional component and a low land use area, insect has many potentials. However, it is largely unknown how much land can be saved if we replace current conventional livestock with insects, especially under different climate change scenarios. Here, we examine the land use effectiveness of raising insects as food, together with using other conventional meat sources under different climate scenarios outlined in the Special Report on Emissions Scenarios (A1, A2, B1, B2). Then, the current livestock meat ratio is analyzed to examine the readiness of each country to fulfill its needs. We also simulated land use changes with different proportions of insect meat production. Based on the land use simulation in different SRES scenarios, insect meat would be effective in fulfilling animal-based energy demands. We statistically examined the relationship of livestock land ratio with countries’ variables (GDP, population, forest area, protected area, government efficiency). Based on an analysis involving the use of various meat composition policies in the four SRES scenarios, insect meat with its high efficiency of land use can be more effective in fulfilling animal-based energy demands than other livestock types. However, to achieve food security in the future, it is a necessity that insect meat be used alongside other alternative solutions that are suitable to each country/area.
Exogenous melatonin confers drought stress by promoting plant growth, photosynthetic capacity and antioxidant defense system of maize seedlings

Melatonin is an important biologically active hormone that plays a vital role in plant growth and development. In particular, it has been investigated for its roles in abiotic stress management. The current experiment was carried out to investigate the protective role of melatonin in photosynthetic traits and the antioxidant defense system of maize seedling under drought stress. Maize seedlings were subjected to drought stress (40–45% FC) after two weeks of seedling emergence, followed by a foliar spray (0, 25, 50, 75 and 100 µM) and soil drench of melatonin (0, 25, 50, 75 and 100 µM). Our results indicated that drought stress negatively affected maize seedling and decreased plant growth and development, biomass accumulation, reduced chlorophyll, and carotenoid content, and significantly declined photosynthetic rate and stomatal conductance. On the other hand, reactive oxygen species, soluble protein, and proline content increased under drought stress. However, the application of exogenous melatonin reduced the reactive oxygen species burst and enhanced the photosynthetic activity by protecting from damages through activation of various antioxidant enzymes under drought stress. Foliar application of 100 µM and soil drench of 50 µM melatonin was the most effective treatment concentrations under drought stress. Our current findings hereby confirmed the mitigating potential of melatonin application for drought stress by maintaining plant growth, improving the photosynthetic characteristics and activities of antioxidants enzymes.
Energy Tunneling: A Way to Achieve Highly Sensitive Material Detection With Sub-Wavelength Resolution

The phenomenon of microwave energy tunneling (ET) has been reported in guided microwave structures loaded with either epsilon-near-zero (ENZ) materials or resonant metallic wires [1]-[14]. A bit of confusion sometimes can arise over the term tunneling, which is often used by physicists, so it seems appropriate here to point out the difference between ET and the well-known particle tunneling encountered in quantum mechanics (Figure 1).
Data-Driven Structuring of the Output Space Improves the Performance of Multi-Target Regressors

The task of multi-target regression (MTR) is concerned with learning predictive models capable of predicting multiple target variables simultaneously. MTR has attracted an increasing attention within research community in recent years, yielding a variety of methods. The methods can be divided into two main groups: problem transformation and problem adaptation. The former transform a MTR problem into simpler (typically single target) problems and apply known approaches, while the latter adapt the learning methods to directly handle the multiple target variables and learn better models which simultaneously predict all of the targets. Studies have identified the latter group of methods as having competitive advantage over the former, probably due to the fact that it exploits the interrelations of the multiple targets. In the related task of multi-label classification, it has been recently shown that organizing the multiple labels into a hierarchical structure can improve predictive performance. In this paper, we investigate whether organizing the targets into a hierarchical structure can improve the performance for MTR problems. More precisely, we propose to structure the multiple target variables into a hierarchy of variables, thus translating the task of MTR into a task of hierarchical multi-target regression (HMTR). We use four data-driven methods for devising the hierarchical structure that cluster the real values of the targets or the feature importance scores with respect to the targets. The evaluation of the proposed methodology on 16 benchmark MTR datasets reveals that structuring the multiple target variables into a hierarchy improves the predictive performance of the corresponding MTR models. The results also show that data-driven methods produce hierarchies that can improve the predictive performance even more than expert constructed hierarchies. Finally, the improvement in predictive performance is more pronounced for the datasets with very large numbers (more than hundred) of targets.
An Investigation of Factors Affecting the Success of Regional Financial Management Information System (Case Study of Palangka Raya Government)

Regional Financial Management Information System (SIMDAKEU) is a key e-government application to implement integrated financial management. The objective of this research is to investigate the factors that influence the achievement of the application in Palangka Raya Government. Model of Delone and McLean's information systems success and technology acceptance model (TAM) are applied as the research concept and model. Data were collected through questionnaires from 126 employees of Palangka Raya Government. A Structural Equation Modeling (SEM) approach was applied in this study. The results of this research showed that from 11 hypotheses proposed from eight constructs namely quality of information, system, service, intention to use, net benefit, users' perception about the ease of use and the usefulness, there are 10 hypotheses proven and 1 hypothesis not proven. The quality of information is highly influencing the achievement of regional financial information system based on the research outcomes. The findings of this research can assist the government in developing the regional financial management information system, so the government can maximize the function of the system as a tool for realizing good and clean governance.
Recovery of head and trunk coordination after stroke: temporal characteristics of head and trunk rotation change during the first three months after stroke

Introduction: Studies in healthy individuals have described a clear sequence of head and trunk coordination during horizontal gaze transfers that require whole body movements. For patients after stroke, there is evidence to suggest that sensorimotor integration of postural adjustments and voluntarily head movements may have been modified. The aim of our study was to examine head and trunk coordination, in particular movement initiation in people early after stroke. Methods: We evaluated 6 people with stroke and 6 healthy controls. Subjects with stroke were assessed clinically and in a laboratory setting at three, six and 12 weeks after stroke. Control subjects were also examined at three consecutive time points with the same weekly interval as the stroke group. Participants were asked verbally to rotate their head to the side of preference and look at a visual signal placed at 90° left and right from centre. Markers were attached at standardised positions of the body and 3-D motion recordings were made using CODAmotion. Data analysis consisted of examining the sequence of head and trunk rotation in both groups separately using Wilcoxon signed rank test. Differences in degree of head rotation, shoulder rotation and delay in rotation were analysed between groups and over time by means ofWilcoxon ranked sum test and Friedman analysis respectively. Results: The pattern of movement demonstrated by the healthy controls (2 females, 4 males, median (IQR) age 64 (62-70) years) at all three time points showed rotation of the head before rotation of the shoulders (p=0.028). In comparison, the mildly impaired stroke group (1 female, 5 males; median (IQR) age 70 (65-79) years) showed no significant difference between rotation of the head and shoulder at three weeks after stroke (p=0.075). This pattern changed over time, reflecting the sequence demonstrated by the healthy controls, with a significant start of rotating the head before the shoulders both at six weeks (p=0.046) and at 12 weeks (p=0.028) after stroke.When comparing both groups at the three time points, there was no significant difference in degree of head rotation, shoulder rotation or in delay in rotation. However the stroke group had a relatively smaller variability in degree of head rotation and a larger variability in degree of shoulder rotation in comparison to the healthy controls. The results of the Friedman test with post-hoc analysis showed a significant decrease in degree of head rotation for stroke patients between three and 12 weeks after stroke (p=0.028). Conclusions: We believe this is the first study to evaluate recovery of the sequence of head and trunk coordination during the acute stages following stroke. Our results suggest that people with stroke show a modified coordination pattern early after stroke but recover over time towards the level of healthy subjects. Future research should include more impaired stroke patients as well as evaluate the relation with clinical measures and thus importance in everyday activities.
Every third Kazakhstani medical student regrets the choice of education: A cross-sectional survey in Almaty

Background : Many physicians regret about their choice of profession. However, no studies on this topic have been performed in Central Asia. Objective: To assess the proportion of medical students who regret their choice of education and to study factors associated with this outcome in Kazakhstan. Methods : This is a cross-sectional survey and 2388 medical students of two medical universities in Almaty in 2011-2012 comprised the sample. Multiple logistic regression was applied to study associations between the outcome and associated factors. Results: Altogether, 33.0% of the responders reported that they regret the choice of profession. The university, faculty, year of study, financing of the studies, place of residence, type of education obtained before entering the university, the reason for choosing the medical profession, how the student prepared him/herself for admission to the university, and opinions about tests for selecting future students and about the medical profession all influenced whether a medical students regretted his or her choice of profession. Conclusions: The results suggest that one third of medical students in Almaty, Kazakhstan, regret the choice of medical education. The factors associated with the outcome identified in this study may be used to optimize the recruitment of students in the future.
Dynamic Responses on Spatio-Temporal Variation and Climate Change Derived from GIMMS NDVI 3g+ (1982-2015) in Shendong Coalfield

This study is to investigate the variation of Normalized Difference Vegetation Index (NDVI) in Shendong coalfield and its surrounding ecological environment, understanding the succession law of vegetation. It can be a guide for decision making on natural restoration and artificial rehabilitation. Based on the latest dataset of Global Inventory Modeling and Mapping Studies Advanced Very High Resolution Radiometer derived NDVI (GIMMS NDVI3g+) (January 1982–December 2015, 34 years). Using the method of correlation analysis, partial correlation analysis, coefficient of variation, and the trend analysis, to investigate the vegetation variation on temporal, spatial and the response to climate change. Time series analysis shows that the growing season was extended again in the mining area of Shendong coalfield. The results of correlation and Partial correlation analysis, depicts the Shendong coalfield had a high correlation with air temperature and a low correlation with precipitation. 84.21% area of mining area have a medium fluctuation, 40% area of CK have a relatively high fluctuation. The linear trend analysis indicates that the change trend rate of the mining area is 29.32% smaller than the CK is 38.70%. It is urgent to estimate the consistency of the three version datesets and establish the transformation model of GIMMS NDVI.
Sports Medicine for the Mature Athlete

Introducing a new hobby for other people may inspire them to join with you. Reading, as one of mutual hobby, is considered as the very easy hobby to do. But, many people are not interested in this hobby. Why? Boring is the reason of why. However, this feel actually can deal with the book and time of you reading. Yeah, one that we will refer to break the boredom in reading is choosing sports medicine for the mature athlete as the reading material.
Information Extraction of Traffic Condition from Social Media using Bidirectional LSTM-CNN

Twitter is social media that has become a source of information for real-time traffic condition in Indonesia. Generally, information contained on Twitter is used for shortterm needs, such as to find out the point of congestion at that time. Whereas, the information can be collected and processed for long-term needs, such as congestion-prone points mapping at certain times. This processed information is very useful for city stakeholders. Information extraction is needed to process information in the form of text from social media that is originally unstructured to be structured. NER technique can be applied to obtain entities that represent traffic condition. This study classifies entities into 11 classes with the BIO encoding scheme, namely B_TIME, I_TIME, B_LOCT, I_LOCT, B_COND, I_COND, B_CAUS, I_CAUS, B_WEAT, I_WEAT, B_MISC, I_MISC, and O. The defined classes represent entities of time, location, condition, cause, weather, miscellaneous, and others. This study proposes a solution in the form of model architecture design using deep learning approach. Bidirectional LSTM approach is used to handle word level. While the CNN approach is used to handle character level. The combination of these two deep learning methods accompanied by word embedding produces the value of F-measure 0.789.
$\ell_\infty$ -Gain Analysis of Discrete-Time Positive Singular Systems With Time-Varying Delays

This paper is concerned with the <inline-formula> <tex-math notation="LaTeX">$\ell _\infty $ </tex-math></inline-formula>-gain analysis problem of discrete-time positive singular systems with time-varying delays. By introducing an auxiliary system, a necessary and sufficient positivity condition is proposed for systems. Then, by using of the positivity and linearity, we investigate the monotonic and asymptotic property of the system with time-varying delays. Then, by resorting to the comparing system with constant delays, an explicit expression of the <inline-formula> <tex-math notation="LaTeX">$\ell _\infty $ </tex-math></inline-formula>-gain of discrete-time singular systems with time-varying delays is given in terms of system matrices. The result shows that <inline-formula> <tex-math notation="LaTeX">$\ell _\infty $ </tex-math></inline-formula>-gain of discrete-time positive singular systems with bounded time-varying delays is insensitive to the magnitude of delays.