Miracle-dz/UniFAR-FTUs huggingface dataset:
Impact of lenvatinib on renal function compared to sorafenib for unresectable hepatocellular carcinoma

Abstract Anti-VEGF drugs, such as tyrosine kinase inhibitors, play an important role in systemic therapy for unresectable hepatocellular carcinoma (uHCC). We examined the effects of sorafenib and lenvatinib on proteinuria and renal function. Patients who were administered sorafenib (n = 85) or lenvatinib (n = 52) as first line treatment for uHCC from July 2009 to October 2020, were enrolled in this retrospective observational study. A propensity score analysis including 13 baseline characteristics was performed. Eighty four patients were selected (sorafenib, n = 42; lenvatinib, n = 42) by propensity score matching (one-to-one nearest neighbor matching within a caliper of 0.2). We analyzed changes in estimated glomerular filtration rate (eGFR) during tyrosine kinase inhibitor treatment, as well as the development of proteinuria in both groups. A multivariate analysis was performed to identify predictors of a deterioration of eGFR. At 4, 8, 12, and 16 weeks, ΔeGFR was significantly lower in the lenvatinib group than in the sorafenib group (P < .05). The lenvatinib group showed a significantly higher frequency of proteinuria than the sorafenib group (30.9% vs 7.1%, P = .005) and had a higher rate of decrease in eGFR than the sorafenib group (P < .05). Multivariate analysis revealed that lenvatinib use was the only predictive factor of eGFR deterioration (odds ratio 2.547 [95% CI 1.028–6.315], P = .043). In cases of proteinuria ≤1+ during lenvatinib treatment, eGFR did not decrease. However, eGFR decreased in the long term (>24 weeks) in patients who have proteinuria ≥2+. Lenvatinib has a greater effect on proteinuria and renal function than sorafenib. In performing multi-molecular targeted agent sequential therapy for uHCC, proteinuria and renal function are important factors associated with drug selection after atezolizumab-bevacizumab combination therapy currently used as the first-line treatment.
ImputeNet: Missing Data Imputation with Graph Neural Networks

: Missing data imputation (MDI) is an important upstream work for many scientiﬁc researches. Traditional methods using global statics or building individual predictive models fail to exploit the inner connections between diﬀerent entries and attributes. In this project, we form the MDI problem as an graph edge attribute prediction problem and solve it with a novel graph neural network (GNN) structure which is able to incorporate both node and edge features and predict missing edge features.
A Study of Application Sandbox Policies in Linux

Desktop operating systems, including macOS, Windows 10, and Linux, are adopting the application-based security model pervasive in mobile platforms. In Linux, this transition is part of the movement towards two distribution-independent application platforms: Flatpak and Snap. This paper provides the first analysis of sandbox policies defined for Flatpak and Snap applications, covering 283 applications contained in both platforms. First, we find that 90.1% of Snaps and 58.3% of Flatpak applications studied are contained by tamperproof sandboxes. Further, we find evidence that package maintainers actively attempt to define least-privilege application policies. However, defining policy is difficult and error-prone. When studying the set of matching applications that appear in both Flatpak and Snap app stores, we frequently found policy mismatches: e.g., the Flatpak version has a broad privilege (e.g., file access) that the Snap version does not, or vice versa. This work provides confidence that Flatpak and Snap improve Linux platform security while highlighting opportunities for improvement.
Backup Magnetometer-Only Attitude Estimation Algorithm for Small Satellites

A different approach for attitude filtering integrates the filter with one of the static attitude estimators (e.g. QUEST) such that the filter uses the estimated attitude by this estimator as the measurement. Among several advantages such as being robust and providing fast convergence, this architecture is also useful when several measurements are integrated. In contrast, this approach cannot provide any measurement to the filter when only one vector measurement is available. In this study, a cascaded static attitude estimator and Kalman filter architecture is proposed and it is shown that coarse attitude estimates are possible using only the magnetometer measurements. Results show that the proposed method can estimate the attitude with an accuracy better than 5 deg, specifically if the satellite is not experiencing high angular rates and the sampling frequency for magnetometer measurements is high. Besides providing a standalone solution, the given method can be used as a back-up when a magnetometer-only attitude solution is needed, e.g. when the satellite is in eclipse.
PERBAIKAN METHODOLOGY FOR REQUIREMENTS ENGINEERING TECHNIQUE SOLUTION (MRETS) DENGAN MENAMBAHKAN DELIVERABLES KEDALAM ATRIBUT PROJECT DAN TEKNIK SINGLE SOLUTION

Salah satu permasalahan yang selalu terjadi dalam pengembangan proyek rekayasa perangkat lunak adalah cenderung mengalami penambahan biaya melebihi anggaran dan mengalami keterlambatan waktu. Demikian juga pada saat implementasi, kualitas perangkat lunak tersebut tidak sesuai dengan harapan user. Salah satu alasan dan merupakan prosentase terbesar mengapa proyek perangkat lunak berjalan tidak sesuai dengan harapan adalah pelaksanaan rekayasa kebutuhan yang tidak baik. Penggunaan teknik rekayasa kebutuhan yang sesuai dalam membangun proyek perangkat lunak berpotensi menentukan kesuksesan sebuah proyek rekayasa perangkat lunak. Salah satu penelitian mengenai teknik rekayasa kebutuhan dalam pengembangan rekayasa perangkat lunak adalah melakukan seleksi kombinasi teknik rekayasa kebutuhan yang dilakukan Li Jiang et al (Jiang, 2005). Dalam penelitian tersebut dijelaskan seleksi kombinasi dari teknik rekayasa kebutuhan dengan menggunakan Methodology for Requirements Engineering Technique Solution (MRETS). Penelitian ini adalah melakukan seleksi kombinasi teknik rekayasa kebutuhan berbasis metoda MRETS dengan penambahan atribut proyek Deliverables dan algoritma Rules penerapan Single Solution. Hasil dari penelitian ini adalah kombinasi teknik rekayasa kebutuhan sesuai dengan proses rekayasa kebutuhan. Kontribusi dari penelitian ini adalah efisiensi penggunaan teknik rekayasa kebutuhan.
How Do Orthopaedic Patients Prefer to Be Contacted During a Pandemic?

Introduction Communication with patients is a vital part of the surgical pathway, and when done effectively, it can greatly improve patient outcomes and patient satisfaction and reduce canceled appointments. Different forms of communication work well for different patient demographics, and it is important to optimize communication techniques. We designed a study to review the communication preferences of orthopedic patients during the COVID-19 pandemic. Methods A cross-sectional study was performed by asking patients who were due to undergo orthopedic procedures to answer a questionnaire on their communication preferences, the reminder notice period for appointments, and safety and satisfaction ratings during the COVID-19 pandemic. Results Communication method preferences are influenced by patient factors such as gender and age. Phone calls were the most popular communication method throughout all patient groups, with 61% selecting it as their preference. Younger patients preferred multiple communication methods of phone calls, texts, and emails, whereas the older group had a stronger preference for letters. Letters were more popular among females (28% compared to 10% of males), whereas males had a stronger preference for other communication methods. The majority of patients said they would not have liked a letter prior to their clinic appointment (65%). Of those who indicated a preferred notice period, 73% would have liked five days or less notice prior to their clinic appointment, while 65% would have liked 10-14 days notice prior to their surgery. The average safety rating was 55%. The overall satisfaction rating with the communication process was 71.7%. Conclusion The COVID-19 pandemic has changed patient feelings towards healthcare and, as a result, changed the way healthcare is delivered. Communication method preferences among trauma and orthopedic patients vary and depend on factors such as gender and age. If healthcare departments can optimize their communication processes, they will improve their patient outcomes and enhance their resources.
Enhancement of Four-Wave Mixing and Supercontinuum Generations Aided With Dual Arc-Shaped Fiber With 2D Material

In this research, we demonstrate the use of Tin telluride (SnTe) deposited on dual arc-shaped fiber (DAF) for four-wave mixing (FWM) and supercontinuum (SC) generations. For the FWM generation using SnTe-deposited DAF, the conversion efficiency obtained was −38 dB at a maximum pump power of 1.5 W. The FWM-based system was stable with minimal peak-to-peak fluctuation of only 0.2 dB for 60 minutes. Also, the tunability of the FWM-based system can be observed up to 5.5 nm. A spectrum spanning 221.52 nm was observed for SC generation when pumped by an amplified pulsed signal from the mode-locked fiber laser (MLFL) source. Pulse compression due to nonlinearity effects in the SnTe-deposited DAF allows the SC spectrum to be broadened, resulting in a narrow pulse width of 0.39 ps. With a pump power of 1.5 W, the amplified MLFL had a peak power of 3.6 kW. The SnTe-deposited DAF has a nonlinear coefficient $\gamma $ of 2787.9 W−1km−1. The experimental result demonstrates that SnTe-deposited DAF was an effective nonlinear media to induce the FWM and SC generation.
Risk assessment of outsourcing e-procurement services: integrating SWOT analysis with a modified ANP-based fuzzy inference system

Abstract With electronic procurement solutions becoming increasingly sophisticated, many firms opt to source these services from third-party providers, effectively transferring (outsourcing) significant responsibility to these services companies. This action, however, entails certain risks, which are oftentimes difficult to assess. To guide managerial practice and to advance academic inquiry in this domain, we identify e-procurement risk factors through a strengths, weaknesses, opportunities, threats analysis, grounded in transaction cost economics (TCE), and propose a risk assessment framework based on the opinions of a group of experts. The approach taken is that of a modified analytic network process methodology, combined with a fuzzy inference system, which is versatile enough to accept the expert opinions in different input formats (such as linguistic variables and ranges). The proposed framework has the capability to aggregate expert judgements’ to estimate risk likelihoods, risk severities and risk factor indices, and derive overall risk magnitudes. The multi-method approach was motivated and is illustrated by a real-life case study of an Indian manufacturing company currently in the process of contract renewal with its existing e-procurement service provider.
Stochastic Resource Allocation for Outage Minimization in Random Access with Correlated Activation

A key challenge for random access communications arising in the monitoring of physical phenomena is optimizing the access policy. This is particularly the case when the activity of each sensor is correlated, contrasting with the independence assumption underpinning standard slotted ALOHA schemes. In this paper, we propose a stochastic resource allocation algorithm to reduce outages via maximization of the expected number of sensors that are able to reliably communicate with an access point. Allowing for devices to transmit data over multiple consecutive frames, we show that the proposed algorithm converges with probability one to a locally optimal solution. Moreover, our algorithm significantly outperforms existing methods in terms of the average number of successful transmissions when utilizing successive interference cancellation.
Joint Route Selection and Content Caching in O-RAN Architecture

The Open Radio Access Network (O-RAN) architecture offers flexible association of distributed network elements, i.e., O-RAN elements, for establishing on-demand radio access network (RAN) stacks [1]. In such as distributed architecture, content caching may help relieve network traffic congestion and end-to-end latency. Leveraging the strengths of both O-RAN architecture and content caching is thus essential for reducing network traffic while meeting user’s quality of experience (QoE) requirements. However, integrating content caching into O-RAN architecture is not straightforward as the content placement policy and the O-RAN element association are tightly coupled. In this paper, we investigate the problem of joint O-RAN element association and content placement in the O-RAN architecture, aiming at minimizing the average long-term traffic incurred in the xHaul transport networks. To this end, a line-search based algorithm is proposed to find efficient O-RAN element association solution; meanwhile, a deep reinforcement learning (DRL) based algorithm is proposed to obtain an efficient content placement policy while being able to deal with large action space issue. The efficacy of our proposed framework is confirmed through extensive numerical results.
Cell-Sweeping: A New Paradigm for Cells Deployment in Radio Access Networks

Good network coverage is an important element of Quality of Service (QoS) provision that mobile cellular operators aim to provide. The established requirements for the existing Fifth Generation (5G) and the emerging scenarios for upcoming Sixth Generation (6G) cellular communication technologies highly depend on the coverage quality that the network is able to provide. In addition, some proposed 5G solutions such as densification, are complex, costly, and tend to degrade network coverage due to increased interference which is critical for the cell-edge performance. In this direction, we present a novel concept of cell-sweeping for coverage enhancement in cellular networks. One of the main objectives behind this mechanism relies on overcoming the cell-edge problem which directly translates into better network coverage. In sequence, the concept operation is introduced and compared to the conventional static cell scenarios. These comparisons target mostly the benefits at the cell-edge locations. Additionally, the use of schedulers that take advantage of the sweeping system is expected to extend the cell-edge benefits to the entire network. This is observed when deploying cell-sweeping with the Proportional Fair (PF) scheduler. A 5th-percentile improvement of 125% and an average throughput increase of 35% were obtained through system level simulations. The preliminary results presented in this paper suggest that cell-sweeping can be adopted as an emerging technology for future Radio Access Network (RAN) deployments.
Designing Complex Web Information Systems: Integrating Evolutionary Process Engineering

Corporations across the globe are increasingly considering the importance of user experience and business process design in creation of Web information systems. Designing Complex Web Information Systems: Integrating Evolutionary Process Engineering provides an overview of modern Web application technologies useful to business designers. Containing advanced findings from across the globe, this Premier Reference Source presents cutting-edge research on user experience design methodologies and the design of business processes.
Sports Journalism’s Uncertain Future: Navigating the Current Media Ecosystem in the Wake of the COVID-19 Pandemic

ABSTRACT In March 2020, the sporting landscape was paused indefinitely due to the COVID-19 pandemic. To understand how the job function and routines of newspaper sports journalists were impacted during the initial U.S. outbreak (March to July 2020), semi-structured in-depth interviews with 23 members of United States (US) print sports media were conducted. Interviewee responses elucidated three main themes: the future of sports journalism is unknown and frightening for those working in the industry, COVID-19 illustrates the importance of interpersonal relationships to produce quality stories, and COVID-19 validates the importance of quality sports journalism. Additionally, interviewees also shed light on the impact that videoconference interviews, specifically those conducted over Zoom, have on the sports journalism field. Even though it was deemed a useful tool during the pandemic, sportswriters feared that teams will continue to limit access by relegating all interviews to Zoom, thus drastically changing the norms of sports journalism. The theoretical implications of these findings are discussed.
A variable-size shallow trench isolation (STL) technology with diffused sidewall doping for submicron CMOS

A shallow trench isolation (STI) technology, RIE (reactive ion etching), CVD (chemical vapor deposition) oxide fill, and polarization are used to realize lithography-limited, submicron device and isolation dimensions. A novel boron diffusion technique is used for nMOSFET field doping, so that the parasitic sidewall inversion (leakage) problem is eliminated. It is shown that both the channel width bias and the narrow channel effect are greatly reduced in the STI technology. The diffused field also allows the boron doping to be self-aligned to the n-well with a single masking step in CMOS. STI is used in conjunction with a MINT (merged isolation and node trench) cell in 16-Mb DRAM (dynamic random access memory) technology. <<ETX>>
Socioeconomic Position and Excessive Daytime Sleepiness: A Systematic Review of Social Epidemiological Studies

The objectives of this empirical study are to describe and discuss the current literature available on the relationship between excessive daytime sleepiness (EDS) and the socioeconomic position (SEP) as well as to provide recommendations for consideration of SEP in sleep medicine and biomedical research. Databases Medline/PubMed, Web of Science, Google scholar and Scopus were screened from January 1990 to December 2020 using PRISMA guidelines and 20 articles were included in the final synthesis. Nineteen studies were cross-sectional and one study was longitudinal. Among these studies, 25.00% (n = 5) are focused on children and adolescent and the remaining 75.00% (n = 15) focused on adults and seniors. Ages ranged from 8 to 18 years old for children/adolescent and ranged from 18 to 102 years old for adults. Main SEP measures presented in these studies were education, income, perceived socioeconomic status and employment. The sample size in these studies varied from N = 90 participants to N = 33,865 participants. Overall, a lower educational level, a lower income and full-time employment were associated with EDS. Symptoms of EDS are prevalent in women, especially those with a low income or no job; and children and adolescents with difficult living conditions or working part time reported more sleep disturbances. SEP is already considered as an important determinant for many health outcomes, but if SEP is embedded in the experimental design in psychosomatic research, biomedical research and clinical practice as a constant variable regardless of outcome; it will move forward future investigations.
Distributed intelligent railway traffic control based on fuzzy decision-making

A multileveled distributed railway traffic control system, which overcomes the drawbacks of conventional centralized railway traffic control systems, is proposed in this paper. The system structure, function distribution and interactions among different hierarchies of the proposed system is addressed in detail. The intelligent control algorithm corresponding to the system is also put forward in detail. The algorithm, which is based on distributed intelligence, knowledge engineering and fuzzy multi-attribute decision-making, can realize the control strategy traffic control. The feasibility of the approach proposed has been proved by simulations. <<ETX>>
A Batched Bayesian Optimization Approach for Analog Circuit Synthesis via Multi-Fidelity Modeling

Device sizing is a challenging problem for analog circuit design. Traditional methods depend on domain knowledge and intensive simulations to search for feasible parameters. Recent studies apply the Bayesian optimization (BO) and a Gaussian process (GP) model in analog circuit synthesis to improve efficiency. The BO framework automatically selects the parameter candidates by inferring the surrogate GP model. However, naive BO employs a sequential updating strategy which is inefficient in a multicore environment. Besides, the widely used GP model requires costly high fidelity data, which are obtained from fine simulations. In this article, we propose a constrained batch BO approach with a multifidelity (MF) model to solve the above difficulties. The batch BO exploits parallel computing and selects promising parameters by multiple acquisition function ensemble. In addition, the MF GP model adapts the low fidelity data obtained from coarse simulations. Specifically, the proposed method incorporates information gain in a weighted clustering algorithm to refine the parameter candidates. As a result, the proposed method maintains the candidates’ quality and diversity, which speeds up the optimization convergence. In the experiments, we demonstrate the efficiency of the proposed approach on three real-world circuits. The results show that our approach reduces the simulation costs by at least 54.6% compared to the state-of-the-art baselines.
Effect of Gravidity on Cardiovascular Markers in Normotensive Pregnant Women

Gravidity, or the number of pregnancies a woman has had, is linked to a number of biochemical alterations, including changes in cardiovascular parameters. These modifications may increase the likelihood of cardiovascular disease in this population. The aim of this research was to evaluate the effect gravidity has on some cardiovascular markers among normotensive pregnant women. A cross-sectional study of 100 women of reproductive age was carried out at Rivers State University and Rivers State University Teaching Hospital, the subjects were chosen at random for the study. Blood samples were taken and tested for total cholesterol, triglycerides, high density lipoprotein, uric acid, and Apolipoprotein A1 and B. Apolipoprotein A1 and B were all measured in blood samples for biochemical analysis. The levels of low density lipoprotein and very low density lipoprotein were determined. Graph Pad Prism Version 8.0. 2.263 was used to analyze the data from the study. Result gotten from the study showed that Gravidity had no significant effect on biochemical parameters (TC, TG, UA, LDL, Apo A1, Apo B, CRP, and VLDL) in pregnant women (P>0.05), but there was a significant increase (P<0.05) in HDL levels among the group; 0.87 ± 0.21 (1-2), 0.93 ± 0.21 (3-4), 0.86 ± 0.12(5-6) and 1.30 ± 0.00 for (7-8). The effect of gravidity (1-2, 3-4, 5-6, 7-8) on HDL was shown to be significant for ANOVA and Turkey post hoc multiple comparison test; (1-2 vs 7-8) (P= 0.0204) and (5-6 vs 7-8) (P= 0.0250). This study demonstrated that gravidity had little or no effect on the biochemical parameters but increases the HDL cholesterol level in normotensive pregnant women.