Composite screener for androgen deficiency related to the aging males’ symptoms scale

Objective.?Methodological characteristics of the Aging Males’ Symptoms (AMS) scale point towards a high standard measurement and comparison of health-related quality of life (HRQoL) over time or intervention. However, the scale was neither developed nor standardized as a screening instrument for androgen deficiency.

Methods.?Data of the Austrian ANDROX study suggested to develop a composite screener for androgen deficiency based on AMS, age, and BMI, to determine sensitivity and specificity to detect low total testosterone (TT) levels. The findings were compared with those of an independent sample of urological patients with suspicion of androgen deficiency (AD) from Germany (n = 803).

Results.?A graphical solution for a composite-screening tool was proposed, with three levels of suspicion for AD: positive screening result (high suspicion), equivocal result, and negative screening result (no suspicion, AD unlikely). The percentage of TT values < 4 ng/ml were 18.7%, 40.7% and 58.8% in the three categories: negative, equivocal and positive, respectively. The findings were confirmed in the independent German sample. In both instances, neither sensitivity nor specificity was very high, i.e., between about 50% and 75%.

Conclusion.?The results of the development and initial validation of the new screener are promising. Further information, and experience from the practice, is needed to confirm or refute the hypothesis that this screener is a useful tool for medical practice.     

Staying safe and visible via message sharing in online social networks

As an imperative channel for fast information propagation, online social networks (OSNs) also have their defects. One of them is the information leakage, i.e., information could be spread via OSNs to the users whom we are not willing to share with. Thus the problem of constructing a circle of trust to share information with as many friends as possible without further spreading it to unwanted targets has become a challenging research topic but still remained open. Our work is the first attempt to study the Maximum Circle of Trust problem seeking to share the information with the maximum expected number of poster’s friends such that the information spread to the unwanted targets is brought to its knees. First, we consider a special and more practical case with the two-hop information propagation and a single unwanted target. In this case, we show that this problem is NP-hard, which denies the existence of an exact polynomial-time algorithm. We thus propose a Fully Polynomial-Time Approximation Scheme (FPTAS), which can not only adjust any allowable performance error bound but also run in polynomial time with both the input size and allowed error. FPTAS is the best approximation solution one can ever wish for an NP-hard problem. We next consider the number of unwanted targets is bounded and prove that there does not exist an FPTAS in this case. Instead, we design a Polynomial-Time Approximation Scheme (PTAS) in which the allowable error can also be controlled. When the number of unwanted targets are not bounded, we provide a randomized algorithm, along with the analytical theoretical bound and inapproximaibility result. Finally, we consider a general case with many hops information propagation and further show its #P-hardness and propose an effective Iterative Circle of Trust Detection (ICTD) algorithm based on a novel greedy function. An extensive experiment on various real-world OSNs has validated the effectiveness of our proposed approximation and ICTD algorithms. Such an extensive experiment also highlights several important observations on information leakage which help to sharpen the security of OSNs in the future.     

Students‘ perceptions of professional social work ethics and the need for the development of competence-based ethics standards in undergraduate training program in Vietnam

As a newly recognized profession in Vietnam over the last two decades social work has undergone significant development, both in training and practice. However, there are many challenges in its professionalization, in which ethics plays a key role. This article presents the key findings of a study about students‘ perceptions of ethics and developing competence-based ethical standards in social work programs. It first analyses the students‘ attitudes and understanding of professional ethics. Second, it clarifies the situation of ethics education in training institutions. Finally, it provides suggestions for the implementation of social work competence-based ethical standards for Vietnam and beyond.     

Flood risk mapping and analysis using an integrated framework of machine learning models and analytic hierarchy process

In this study, a new approach of machine learning (ML) models integrated with the analytic hierarchy process (AHP) method was proposed to develop a holistic flood risk assessment map. Flood susceptibility maps were created using ML techniques. AHP was utilized to combine flood vulnerability and exposure criteria. We selected Quang Binh province of Vietnam as a case study and collected available data, including 696 flooding locations of historical flooding events in 2007, 2010, 2016, and 2020; and flood influencing factors of elevation, slope, curvature, flow direction, flow accumulation, distance from river, river density, land cover, geology, and rainfall. These data were used to construct training and testing datasets. The susceptibility models were validated and compared using statistical techniques. An integrated flood risk assessment framework was proposed to incorporate flood hazard (flood susceptibility), flood exposure (distance from river, land use, population density, and rainfall), and flood vulnerability (poverty rate, number of freshwater stations, road density, number of schools, and healthcare facilities). Model validation suggested that deep learning has the best performance of AUC = 0.984 compared with other ensemble models of MultiBoostAB Ensemble (0.958), Random SubSpace Ensemble (0.962), and credal decision tree (AUC = 0.918). The final flood risk map shows 5075 ha (0.63%) in extremely high risk, 47,955 ha (5.95%) in high-risk, 40,460 ha (5.02%) in medium risk, 431,908 ha (53.55%) in low risk areas, and 281,127 ha (34.86%) in very low risk. The present study highlights that the integration of ML models and AHP is a promising framework for mapping flood risks in flood-prone areas.     

A Note on Optical Network with Nonsplitting Nodes

We study the problem of computing the minimum total weight multicast route in an optical network with both nonsplitting and splitting nodes, and present a simple approximation with performance ratio 3, which is better than existing one in the literature.     

Bound and exact methods for assessing link vulnerability in complex networks

Assessing network systems for failures is critical to mitigate the risk and develop proactive responses. In this paper, we investigate devastating consequences of link failures in networks. We propose an exact algorithm and a spectral lower-bound on the minimum number of removed links to incur a significant level of disruption. Our exact solution can identify optimal solutions in both uniform and weighted networks through solving a well-constructed mixed integer program. Also, our spectral lower-bound derives from the Laplacian eigenvalues an estimation on the vulnerability of large networks that are intractable for exact methods. Through experiments on both synthetic and real-world networks, we demonstrate the efficiency of the proposed methods.