Miracle-dz/UniFAR-FTUs huggingface dataset:
Psychiatric and Neurological Recovery After Critical Illness

Research on post-ICU outcomes has progressed from simple descriptions of mortality to patient-centered quality of life measures to detailed epidemiology studies of weakness, impaired cognition and psychiatric disorders. In the last five years, clinicians have demonstrated that it is feasible to conduct randomized intervention trials to improve post-ICU psychological health and functional status. We review the major post-ICU observational and intervention studies completed in the last 15 years; describe plausible causal pathways that lead to impaired post-ICU recovery; and describe changes in patient care that could be done in most ICUs that would likely improve patients’ outcome.
Delay-Sensitive Task Offloading in the 802.11p-Based Vehicular Fog Computing Systems

Vehicular fog computing (VFC) is envisioned as a promising solution to process the explosive tasks in autonomous vehicular networks. In the VFC system, task offloading is the key technique to process the computation-intensive tasks efficiently. In the task offloading, the task is transmitted to the VFC system according to the 802.11p standard and processed by the computation resources in the VFC system. The delay of task offloading, consisting of the transmission delay and computing delay, is extremely critical especially for some delay-sensitive applications. Furthermore, the long-term reward of the system (i.e., jointly considers the transmission delay, computing delay, available resources, and diversity of vehicles and tasks) becomes a significantly important issue for providers. Thus, in this article, we propose an optimal task offloading scheme to maximize the long-term reward of the system where 802.11p is employed as the transmission protocol for the communications between vehicles. Specifically, a task offloading problem based on a semi-Markov decision process (SMDP) is formulated. To solve this problem, we utilize an iterative algorithm based on the Bellman equation to approach the desired solution. The performance of the proposed scheme has been demonstrated by extensive numerical results.
Cyber Vulnerability Intelligence for Internet of Things Binary

Internet of Things (IoT) integrates a variety of software (e.g., autonomous vehicles and military systems) in order to enable the advanced and intelligent services. These software increase the potential of cyber-attacks because an adversary can launch an attack using system vulnerabilities. Existing software vulnerability analysis methods used to be relying on human experts crafted features, which usually miss many vulnerabilities. It is important to develop an automatic vulnerability analysis system to improve the countermeasures. However, source code is not always available (e.g., most IoT related industry software are closed source). Therefore, vulnerability detection on binary code is a demanding task. This article addresses the automatic binary-level software vulnerability detection problem by proposing a deep learning-based approach. The proposed approach consists of two phases: binary function extraction, and model building. First, we extract binary functions from the cleaned binary instructions obtained by using IDA Pro. Then, we employ the attention mechanism on top of a bidirectional long short-term memory for building the predictive model. To show the effectiveness of the proposed approach, we have collected datasets from several different sources. We have compared our proposed approach with a series of baselines including source code-based techniques and binary code-based techniques. We have also applied the proposed approach to real-world IoT related software such as VLC media player and LibTIFF project that used on Autonomous Vehicles. Experimental results show that our proposed approach betters the baselines and is able to detect more vulnerabilities.
Reducing Affective Responses to Surgical Images and Videos Through Stylization

We present the first empirical study on using colour manipulation and stylization to make surgery images/videos more palatable. While aversion to such material is natural, it limits many people's ability to satisfy their curiosity, educate themselves and make informed decisions. We selected a diverse set of image processing techniques to test them both on surgeons and lay people. While colour manipulation techniques and many artistic methods were found unusable by surgeons, edge‐preserving image smoothing yielded good results both for preserving information (as judged by surgeons) and reducing repulsiveness (as judged by lay people). We then conducted a second set of interview with surgeons to assess whether these methods could also be used on videos and derive good default parameters for information preservation. We provide extensive supplemental material at osf.io/4pfes/.
A Comparison of Five Rules for Determining the Number of Components in Complex Patterns

The performance of five methods for determi ning the number of components to retain (Horn' s parallel analy s is, Velicer 1 s MAP, Cattell 1 s SCREE, Bartlett's test and Kaiser ' s eigenvalu e greater than unity) was investigated across seven systematically varied factors (sample size, number of variables, number of component s, component saturation, equal or unequal numbers of var iables per component, and the presence or absence of unique and complex variables). Five sample correlation matrices were genera t ed at each of two levels of sample s ize from the 48 known population correlation matrices representing six levels of component patt ern complexit y. The performance of the parallel analysi s and the MAP methods was generally the best across all situati ons. The SCREE test was generally accurate but variable . Bartlett 's test was less accurate and more variable than the SCREE test. Kaiser ' s method tended to severely overestimate the number of components. Recommendations concerning the condi tions under which the methods are accurate and th e most effective and useful applications of combinations of methods are discuss ed.
Penggunaan e-learning dengan Technology Acceptance Model (TAM)

Kemajuan dalam teknologi informasi memberi kesempatan pada institusi pendidikan untuk mengadopsi teknologi untuk meningkatkan efisiensi pembelajaran. e-Learning merupakan salah satu pengembangan tersebut dan tidak dapat disampaikan tanpa menggunakan teknologi. Tujuan penelitian ini yaitu untuk mendapatkan bukti empiris terkait actual usage dari penggunaan e-learning dengan pemediasi intention to use. Data dalam penelitian ini sebanyak 135 kuesioner yang disebarkan kepada mahasiswa Universitas Airlangga yang sempat memanfaatkan AULA. AULA merupakan portal e-Learning di Universitas Airlangga, yang merupakan singkatan dari Airlangga Univeristy e-Learning Application. Alat uji yang digunakan adalah Warp PLS. Perceived usefulness yang dirasakan pada penggunaan e-learning tidak memberikan pengaruh pada actual usage. Perceived ease of use memiliki hubungan signifikan pada intention to use. Hasil pengujian pengaruh tidak langsung menunjukkan perceived usefulness mempengaruhi niat perilaku untuk menggunakan teknologi. Persepsi kemudahan menggunakan teknologi dimotivasi tingkat kepercayaan individu terhadap kemampuan menggunakan teknologi, yang mana akan mendorong persepsi kebermanfaatan dan berimplikasi pada niat untuk menggunakan teknologi untuk menggunakan e-learning.Kata kunci: Actual Usage, perceived ease of use, e-Learning, intention to use Actual usage use of e-learning with Technology Acceptance Model (TAM) AbstractProgress in information technology provides opportunities for education to encourage technology to improve learning efficiency. E-Learning is one such development and cannot be delivered without using technology. The purpose of the study is to get empirical evidence related to actual usage of using e-learning with intention to use as a mediation. Data used in the study were 135 questionnaires that distributed to students of Airlangga University who are active or have used / participated in AULA (Airlangga University e-Learning Application). AULA is an e-Learning portal at Airlangga University. Data analysis techniques using Warp PLS. The results show the perceived usefulness of e-learning, does not affect the actual use. Perceived ease of use has a significant positive relationship with intention to use. The results evaluation direct effect of perceived usefulness influences intention to use technology. Perceived ease of use of technology is motivated by the level of individual trust in ability to use technology, which will encourage perceptions of usefulness and have implications for the intention to use technology to use e-learning.Keywords: Actual Usage, perceived ease of use, e-learning, intention to use
Knowledge of, attitudes toward, and barriers to participation of colorectal cancer screening in Aydın central region

Summary Objective: Colorectal cancer (CRC), which ranks third in cancer morbidity and second in cancer deaths worldwide, can be detected early and prevented with mass screening programs. Improving community awareness of CRC is crucial for the success of these programs. This study investigated the as- sociation of screening test participation with knowledge of, attitudes toward, and barriers to CRC and screening tests in Aydin central region. Methods: In a one-month period in 2012 (March) person-to-person in- terviews by using a standardized survey instrument were conducted with 562 subjects aged 50 years and older who were randomly recruited from eight family medicine centers (FHCs) in Aydin central region. Eight fam- ily health centers were randomly determined among 24 FHCs in the re- gion. The study questionnaire included items questioning the screening participation status, knowledge of, attitudes toward, and barriers to CRC and screening tests, and intent to participate. Results: The mean age of the participants was 59.8±7.4 years (range, 50-80 years), and 66.9% (376 participants) were male. One hundred forty six par- ticipants (25.8%) had knowledge about CRC and 68 participants (12.1%) knew that CRC could be diagnosed early. Of the participants, 32 (5.7%) knew colonoscopy and 13 (2.3%) fecal occult blood testing (FOBT) as a screening method. A total of 66 (11.9%) of participants had undergone pre- vious CRC testing (FOBT 7.7%; sigmoidoscopy 3.6% and colonoscopy 5.4%). Only 25.9% (145 subjects) of the respondents received physician rec- ommendations to undergo CRC testing and 67.3% (105 subjects) of them obeyed the recommendation. Age (p=0.009), health insurance (p=0.009), being diagnosed with any kind of cancer (p 0.05), those participants knowing colonoscopy as a screen- ing test underwent more screening (p<0,01). Although 39.3% (221 respond- ents) perceived need for screening, most respondents responded (66.0%; 371 subjects) positively to undergo future CRC testing. The most frequently reported barriers to getting CRC screening tests were not knowing CRC and screening tests (182 subjects, 32.4%) and not seeing themselves at high risk (164 subjects, 29.2%). Conclusion: Our results demonstrate that people applying to regional FHCs lack of knowledge of CRC and screening tests recommended for those older than 50 years are neither sufficiently known nor used. Physicians do not suf- ficiently recommend for the screening tests, whereas the recommendations are practiced well. General knowledge of CRC don't seem to affect behav- iours, however more specific knowledge effects them positively.
Mapping heuristics and prospect theory: A study of theory integration

Efforts to model boundedly rational risky choice have generated two influential but separate lines of research: cumulative prospect theory (CPT) and heuristics. Each approach has pursued its own research questions, and both have made important contributions to the study of decision making under risk, but these contributions have hardly been connected to each other. In this chapter, I illustrate how the two approaches can be brought together. Specifically, I show how the choices produced by heuristics of risky choice are reflected in CPT’s value and weighting functions, and how CPT can be used to reveal and measure how the properties of choices produced by some heuristics are contingent on the structure of the environment. Finally, I discuss how empirical choice phenomena (e.g., the fourfold pattern of risk attitudes) that have critically shaped key assumptions in CPT might result from heuristic information processing, and how insights into the boundary conditions of heuristic information processing can in turn suggest moderating conditions for those choice phenomena. These analyses highlight the value of elaborating the relationships between theories in order to pursue theory integration.
Distal triceps ruptures

Injury to the distal triceps is uncommon and often associated with anabolic steroid use, weight-lifting, or laceration. Eccentric loading of a contracting triceps has been implicated, particularly in professional athletes. Initial diagnosis may be difficult because a palpable defect is not always present. Pain and swelling may further limit the ability to evaluate strength and elbow range of motion. MRI may confirm the diagnosis and guide management. Treatment for incomplete tears with retained active elbow extension against resistance is nonoperative. Operative repair is indicated in active individuals with complete tears or incomplete tears with loss of strength. The results of operative repair are reported to be good to excellent and even operative repair of chronic tears can yield good results.
Comparing The Effectiveness Of Using Tablet Or Desktop PC in Video-Supported Education

Software courses include a variety of mathematical, technical or graphical skills. Therefore, students need to accomplish different educational practices to be successful. They should struggle with the fast paces of the lectures during the active course times. It is always hard to both understand the theoretical content of coding and use it to create practical solutions. Video records of the lectures can be used as supportive instructional technologies to improve the software skills of the students. In this concept, the main purpose of the study was defined as comparing the effectiveness of Using Tablet or Desktop PC in Video-Supported Education. This is a part of scientific Project (Project Number: 2012-09-03-KAP1) financially supported by Scientific Research Project Office of Yildiz Technical University. It was conducted in two different video-supported software courses at undergraduate level. The effect of students’ access to video lectures via tablet or desktop computer is investigated in 15 weeks in total. The application was used in Programming Languages Course at undergraduate 2. Grade and in Multimedia Design Course at undergraduate 3. Grade. 15 videos for each course, 30 video lecture records in total, were published on http://www.ytuavitab. com website which was prepared and developed by researchers. The obtained findings demonstrated that the academic success of the students who accessed video lectures via Tablet PC were significantly higher than the other students for both Multimedia Design and Programming Languages Courses. The obtained finding can be explained as Tablet PC usage can be performed independently of the current environment.
Review and Benchmarking of Precision-Scalable Multiply-Accumulate Unit Architectures for Embedded Neural-Network Processing

The current trend for deep learning has come with an enormous computational need for billions of Multiply-Accumulate (MAC) operations per inference. Fortunately, reduced precision has demonstrated large benefits with low impact on accuracy, paving the way towards processing in mobile devices and IoT nodes. To this end, various precision-scalable MAC architectures optimized for neural networks have recently been proposed. Yet, it has been hard to comprehend their differences and make a fair judgment of their relative benefits as they have been implemented with different technologies and performance targets. To overcome this, this work exhaustively reviews the state-of-the-art precision-scalable MAC architectures and unifies them in a new taxonomy. Subsequently, these different topologies are thoroughly benchmarked in a 28nm commercial CMOS process, across a wide range of performance targets, and with precision ranging from 2 to 8 bits. Circuits are analyzed for each precision as well as jointly in practical use cases, highlighting the impact of architectures and scalability in terms of energy, throughput, area and bandwidth, aiming to understand the key trends to reduce computation costs in neural-network processing.
RT-22MRI AND FET PET FOR RADIOTHERAPY PLANNING IN RECURRENT HIGH-GRADE GLIOMA (HGG) IN A PROSPECTIVE PHASE I TRIAL

BACKGROUND AND PURPOSE: Re-irradiation of HGG at recurrence may be a viable treatment option for some patients. Positron emission tomography (PET) using the amino acid tracer, 18F-fluoro-ethyltyrosine (FET) may have higher specificity and sensitivity than MRI in this setting. Both FET PET and MRI were used for target delineation in a prospective trial. The purpose of this study was to evaluate the impact of FET PET on the radiotherapy target. MATERIAL AND METHODS: A phase I trial examined the safety of hypofractionated stereotactic re-irradiation at different dose levels. Patients in PS 0-2 with localized recurrence of HGG and no other treatment options were eligible. With MRI, tumor was manually contoured using T1 contrast enhanced sequences. For PET, a threshold of 1.6x mean in background was used in a semi-automatic segmentation procedure. The planning target volume for treatment was the combination of both tumor volumes (MRI and PET) plus a 2 mm margin. Matlab software was used for spatial analyses. (Trial identifier: NCT02025231). RESULTS: Twenty-eight patients were included (GBM: n = 22; grade 3 glioma: n = 6). All patients had received radiotherapy and temozolomide, and 61 % had previously received bevacizumab. Median tumor volume defined by MRI and PET was 34 cm3 (range: 0-230 cm3) and 24 cm3 (range:0-214 cm3), respectively. Using PET increased the total gross tumor volume by a median of 10 cm3 (range:0-77 cm3), compared to MRI alone. The median longest distance from the MRI-target to encompass the PET-target was 10 mm (range: 0.6 to 43 mm). CONCLUSION: Tumor volumes defined by MRI and PET were spatially separated by up to 43 mm indicating that large portions of PET positive tumor would be missed if the target was solely based on MRI (T1 + contrast). FET PET may be useful for tumor delineation in re-irradiation of HGG.
Discrete Calabi Flow: A Unified Conformal Parameterization Method

Conformal parameterization for surfaces into various parameter domains is a fundamental task in computer graphics. Prior research on discrete Ricci flow provided us with promising inspirations from methods derived via Riemannian geometry, which is rigorous in theory and effective inpractice. In this paper, we propose a unified conformal parameterization approachfor turning triangle meshes into planar and spherical domains using discrete Calabi flow onpiecewise linear metric. We incorporate edge‐flipping surgery to guarantee convergence as well as other significant improvements including approximate Newton's method, optimal step‐lengths, priority embedding and boundary customizing, which achieve better performance and functionality with robustness and accuracy.
Wiretap Channels With Random States Non-Causally Available at the Encoder

We study the state-dependent (SD) wiretap channel (WTC) with non-causal channel state information (CSI) at the encoder. This model subsumes all instances of CSI availability as special cases, and calls for an efficient utilization of the state sequence for both reliability and security purposes. A lower bound on the secrecy-capacity, that improves upon the previously best known result published by Prabhakaran et al., is derived based on a novel superposition coding scheme. Our achievability gives rise to the exact secrecy-capacity characterization of a class of SD-WTCs that decompose into a product of two WTCs, one independent of the state and the other depends only on the state. The results are derived under the strict semantic-security metric that requires negligible information leakage for all message distributions.
Transformational leadership and employee knowledge sharing: explore the mediating roles of psychological safety and team efficacy

Purpose This paper aims—based on past research works which have shown that transformational leadership has positive impact on knowledge sharing—to explore the impact of different leadership dimensions of transformational leadership on knowledge sharing and further to explore the mechanism through which transformational leadership affects employee knowledge sharing in China. Design/methodology/approach Based on the transformational leadership theory and the team learning theory, it is proposed that all four dimensions of transformational leadership, including intellectual stimulation, individualized consideration, inspirational motivation and idealized influence, have unique impact on employee knowledge sharing. It is further proposed that psychology safety and team efficacy mediate these relationships. Then data were collected from over 400 employees from knowledge-based companies in China to empirically test the proposed relationships with the method of structural equation modeling. Findings The results show that psychological safety fully mediated the impact of intellectual stimulation on knowledge sharing, and team efficacy fully mediated the impact of inspirational motivation on knowledge sharing. Both factors also mediated the impact of individualized consideration on knowledge sharing. The results thus provide empirical support for the impact of transformational leadership on employee knowledge sharing in an international context. Originality/value The past years have seen increasing interest in leadership and knowledge sharing in emerging markets, yet the mechanism through which leadership affects employee knowledge sharing remains understudied. This study explores the impact of different dimensions of transformational leadership on employee knowledge sharing, and further shows that psychological safety and team efficacy mediate these relationships in a collectivistic society where knowledge sharing is consistent with cultural norms. The findings help develop more robust knowledge sharing theories in the international context and provide insightful suggestions for management practitioners in emerging markets.
Karp-Sipser based kernels for bipartite graph matching

We consider Karp–Sipser, a well known matching heuristic in the context of data reduction for the maximum cardinality matching problem. We describe an eﬃcient implementation as well as modiﬁcations to reduce its time complexity in worst case instances, both in theory and in practical cases. We compare experimen-tally against its widely used simpler variant and show cases for which the full algorithm yields better performance.
3D Model Visualization for Brain Tumour using MRI Images

The inaccurate prediction of tumour is because of the 2D images do not present the complete natural tumour representation as in 3D visualization. In order to construct the 3D model, the contour of 2D MRI images must be merged together. In this work, the edge detection of brain tumour on 2D images is done using the Geodesic Active Contour (GAC) model based on Additive Operator Splitting (AOS), then 3D model is visualized using Image Manifold (IM) and Volume Estimation (VE) methods. The comparison of performance for both methods is calculated. In conclusion, the execution time for VE method is higher than IM method since more images are used in VE method to calculate the volume of the tumour accurately. In terms of iteration number, Volume Estimation has a higher number of iterations, but for error and root mean square error, both methods have roughly the same value.