We study a fair division problem in (multi)graphs where n agents (vertices) are pairwise connected by items (edges), and each agent is only interested in its incident items. We consider how to allocate items to incident agents in an envy-free manner, i.e., envy-free orientations, while minimizing the overall payment, i.e., subsidy. We first prove that computing an envy-free orientation with the minimum subsidy is NP-hard, even when the graph is simple and the agents have bi-valued additive valuations. We then bound the worst-case subsidy. We prove that for any multigraph (i.e., allowing parallel edges) and monotone valuations where the marginal value of each good is at most $1 for each agent, $1 each (a total subsidy of n-1, where n is the number of agents) is sufficient. This is one of the few cases where linear subsidy Θ(n) is known to be necessary and sufficient to guarantee envy-freeness when agents have monotone valuations. When the valuations are additive (while the graph may contain parallel edges) and when the graph is simple (while the valuations may be monotone), we improve the bound to n/2 and n-2, respectively. Moreover, these two bounds are tight.

Cake cutting is a widely studied model for allocating resources with temporal or spatial structures among agents. Recently, a new line of research has emerged that focuses on the discrete variant, where the resources are indivisible and connected by a path. In some real-world applications, the resources are interdependent, and dividing the cake may reduce their effectiveness. In this paper, we introduce a model that captures the effect of division as switching utility loss and investigate the tradeoff between fairness and efficiency for various settings. Specifically, we measure fairness and efficiency using the popular notions of envy-freeness up to one item (EF1) and social welfare, respectively. The goal of our study is to understand how much social welfare must be sacrificed to ensure EF1 allocations and design polynomial-time algorithms that can compute EF1 allocations with the best possible social welfare guarantee.

We study the envy-free house allocation problem when agents have uncertain preferences over items and consider several well-studied preference uncertainty models. The central problem that we focus on is computing an allocation that has the highest probability of being envy-free. We show that each model leads to a distinct set of algorithmic and complexity results, including detailed results on (in-)approximability. En route, we consider two related problems of checking whether there exists an allocation that is possibly or necessarily envy-free. We give a complete picture of the computational complexity of these two problems for all the uncertainty models we consider.

The concerns on the function of Transmembrane protein 173 (TMEM173)-dependent innate immunity in prevention and management of cancers has recently been increased. The role of TMEM173 in predicting the prognosis and response to treatment in lung adenocarcinoma (LUAD) remain unclear. Our study revealed that TMEM173 expression was significantly differential in various tumors and the related prognosis was heterogeneous. Further investigation discovered that the expression level of TMEM173 in LUAD tissues was significantly decreased and high TMEM173 expression is associated with better overall survival in LUAD patients. TMEM173 was mainly enriched in immune response-regulating signaling pathway, T cell activation and cell cycle G2/M phase. Furthermore, it was found that TMEM173 expression was positively related to markers and infiltration levels of tumor-infiltrating immune cells. TMEM173 could predict response to targeted therapy, chemotherapy and immunotherapy in LUAD patients. In vitro TMEM173 knockdown decreased the percentage of G2 phase cells, contributing to the increased growth of lung cancer cells. These results implied that TMEM173 might be a prognostic biomarker and a potential target of precision therapy for LUAD patients.

We study algorithmic fairness in a budget-feasible resource allocation problem. In this problem, a set of items with varied sizes and values are to be allocated to a group of agents, while each agent has a budget constraint on the total size of items she can receive. An envy-free (EF) allocation is defined in this context as one in which no agent envies another for the items they get and, in addition, no agent envies the charity, who is automatically endowed with all the unallocated items. Since EF allocations barely exist even without budget constraints, we are interested in the relaxed notion of envy-freeness up to one item (EF1). In this paper, we further the recent progress towards understanding the existence and approximations of EF1 (or EF2) allocations. We propose a polynomial-time algorithm that computes a 1/2-approximate EF1 allocation for an arbitrary number of agents with heterogeneous budgets. For the uniform-budget and two-agent cases, we present a polynomial-time algorithm that computes an exact EF1 allocation. We also consider the large budget setting, where the item sizes are infinitesimal relative to the agents’ budgets. We show that both the allocations that maximize the Nash social welfare and the allocations that our main algorithm computes are EF1 in the limit.

Students who have been taught new ideas need to develop their skills by carrying out further work in their own time. This often consists of a series of exercises which must be completed. While students can choose exercises themselves from online sources, they will learn more quickly and easily if the ex-ercises are specifically tailored to their needs. A good teacher will always aim to do this, but with the large groups of students who typically take advantage of open online courses, it may not be possible. Exercise prediction, working with large-scale matrix data, is a better way to address this challenge, and a key stage within such prediction is to calculate the probability that a student will answer a given question correctly. Therefore, this paper presents a novel approach called Weighting-based Student Ex-ercise Matrix Factorization (Wse-MF) which combines student learning ability and exercise difficulty as prior weights. In order to learn how to complete the matrix, we apply an iterative optimization method that makes the approach practical for large-scale educational deployment. Compared with eight models in cognitive diagnosis and matrix factorization, our research results suggest that Wse-MF significantly outperforms the state-of-the-art on a range of real-world datasets in both prediction quality and time complexity. Moreover, we find that there is an optimal value of the latent factor K (the inner dimension of the factorization) for each dataset, which is related to the relationship between skills and exercises in that dataset. Similarly, the optimal value of hyperparameter c 0 is linked to the ratio between exercises and students. Taken as a whole, we demonstrate improvements to matrix factorization within the context of educational data. (c) 2023 The Author(s). Published by Elsevier Ltd. This is an open access article under the CC BY-NC-ND license ( http://creativecommons.org/licenses/by-nc-nd/4.0/ )

Knowledge tracing is an important research topic in student modeling. The aim is to model a student’s knowledge state by mining a large number of exercise records. The dynamic key-value memory network (DKVMN) proposed for processing knowledge tracing tasks is considered to be superior to other methods. However, through our research, we have noticed that the DKVMN model ignores both the students’ behavior features collected by the intelligent tutoring system (ITS) and their learning abilities, which, together, can be used to help model a student’s knowledge state. We believe that a student’s learning ability always changes over time. Therefore, this article proposes a new exercise record representation method, which integrates the features of students’ behavior with those of the learning ability, thereby improving the performance of knowledge tracing. Our experiments show that the proposed method can improve the prediction results of DKVMN.

Cognitive diagnosis methods need to assess the students' skills to provide personalized exercise recommendation. To perform this assessment, an initially hand built Q-matrix are presented to students, which would affect the recommendation results in intelligence education. However, very few previous studies have examined this exercise recommendation task on utilizing the implicit skills among exercises, in which the opinions of implicit skill might carry extra specific knowledge. We propose a data-driven frame to reconstruct Q-matrix automatically from implicit skills perspective and explore the utility of Dynamic Key-Value Memory Networks to solve this task. Experimental results demonstrate that our method has a guiding significance in pedagogical theory.

BACKGROUND:The alterations of lipid profile in cancer has been reported to be associated with cancer development. However, the prognostic value of serum lipid markers level in cancer is currently under debate. Here we performed a meta-analysis to investigate the prognostic significance of serum blood total cholesterol (TC), Triglycerides (TG), high-density lipoprotein cholesterol (HDL-C) and low-density lipoprotein cholesterol (LDL-C) for cancer. METHODS:We systematically searched in PubMed and EMBASE for follow-up studies to evaluate the association between blood TC, TG, HDL-C, LDL-C and overall survival (OS) or disease-free survival (DFS) in patients with cancer. Pooled hazard ratio (HR) and 95% CIs were pooled using the random models. Subgroup and sensitivity analyses were also performed. RESULTS:Twenty-six studies including 24655 individuals were identified. For patients with higher TC before diagnosis, the summary HR were 0.82 (95% CI 0.75-0.90) for OS, 0.920 (95% CI, 0.849-0.997) for DFS. Patients with higher HDL-C had a 37% reduced risk of death compared with lower HDL-C (HR 0.63, 95%CI 0.47-0.86, P<0.001). As for DFS, patients with higher HDL-C level had the risk of disease relapse reduced by 35% (HR 0.65, 95% CI, 0.48-0.89, P<0.001) compared with patients with lower levels. CONCLUSIONS:After pooled analysis, only TC and HDL-C were significantly associated with cancer survival. Our findings demonstrate for the first time that serum TC and HDL-C was identified as a protective factor for overall survival in cancer patients.

The oxyguanine glycosylase 1 (OGG1) gene has an important role in DNA repair, and the polymorphism of the gene may alter cancer susceptibility. This study aims to examine the association between the OGG1 Ser326Cys polymorphism and cancer risk based on meta-analysis. Relevant studies were identified through a search of PubMed and Weipu databases, and a total of 109 studies including 111 comparisons containing 34,041 cases and 42,730 controls were enrolled. Overall, significant association was observed between OGG1 Ser326Cys polymorphism and cancer risk in all genetic models except for heterozygote model (Cys/Cys + Cys/Ser vs Ser/Ser: OR 1.071, 95 % CI 1.019–1.125; Cys/Cys vs Cys/Ser + Ser/Ser: OR 1.159, 95 % CI 1.076–1.248; Cys/Cys vs Ser/Ser: OR 1.202, 95 % CI 1.105–1.308). In stratified analysis by cancer type, significantly increased cancer risk was observed in digestive system cancer, head and neck cancer and lung cancer. For gynecologic cancer, significantly increased cancer risk was also observed in homozygote model (OR 1.974, 95 % CI 1.254–3.107). In addition, in stratified analysis by ethnicities, increased cancer risk was found in Asians (Cys/Cys vs Cys/Ser + Ser/Ser: OR 1.195, 95 % CI 1.088–1.313; Cys/Cys + Cys/Ser vs Ser/Ser: OR 1.115, 95 % CI 1.045–1.190; Cys/Cys vs Ser/Ser: OR 1.273, 95 % CI 1.149–1.410). The OGG1 Ser326Cys polymorphism may be a risk factor for cancers of lung, digestive system and head and neck.

Cooperative games provide an appropriate framework for fair and stable profit distribution in multiagent systems. In this paper, we study the algorithmic issues on path cooperative games that arise from the situations where some commodity flows through a network. In these games, a coalition of edges or vertices is successful if they establish a path from the source to the sink in the network, and lose otherwise. Based on dual theory of linear programming and the relationship with flow games, we provide the characterizations on the CS-core, least-core and nucleolus of path cooperative games. Furthermore, we show that the least-core and nucleolus are polynomially solvable for path cooperative games defined on both directed and undirected network.

BACKGROUND:DNA damage, caused by numerous carcinogens, contributes to the increased risk of different types of cancer. The base excision repair (BER) pathway including the apurinic/apyrimidic endonuclease (APE1, also known as APEX1) gene plays an important role in preventing the accumulation of DNA damage and maintaining genomic stability. The aim of the present study is to determine whether polymorphisms of APE1 are associated with the risk of prostate cancer (PCa) in the Chinese Han population.METHODS:This study consisted of 198 patients with PCa and 156 healthy controls. The polymorphisms of APE1, Asp148Glu (rs1130409) and -141T/G (rs1760944) were determined by the polymerase chain reaction and restriction fragment length polymorphism (PCR-RFLP) method.RESULTS:The genotypic distributions of the two polymorphisms in controls were in Hardy-Weinberg equilibrium (p = 0.92 and p = 0.83, respectively). Logistic regression analysis indicated that the -141GG genotype was significantly associated with a decreased risk of PCa compared with the -141TT genotype (p = 0.03; OR 0.49; 95% CI 0.26 - 0.92). The G allele was also significantly associated with a reduced risk of PCa compared with the T allele (p = 0.02; OR 0.71; 95% CI 0.52 - 0.96). However, no association between Asp148Glu polymorphism and the risk of PCa was found.CONCLUSIONS:The -141GG genotype and G allele of the APE1 gene are associated with a decreased risk of PCa in the Chinese Han population.

Purpose: Laparoscopic Madigan prostatectomy have not been reported yet. We modified the Madigan prostatectomy to make it suitable for laparoscopically enucleating hyperplastic glands larger than 100 g. Patients and Methods: Between May 2007 and Oct 2008, extraperitoneal laparoscopic prostatectomy with maintenance of the intact urethra had been performed on 16 patients with benign prostatic hyperplasia (BPH) and glands than 100 mg. To make it suitable for laparoscopic use, two major modifications had been made: (1) Open the prostate capsule near the bladder neck without sutures along the opening; (2) identify the bladder neck mucosa before recognizing the urethra. All patients were evaluated preoperatively and postoperatively. Data were compared with those from open surgeries. Results: All laparoscopic procedures were successful with the total operative time of 111.8 +/- 28.6 minutes, which had no significant difference compared with open surgeries. Estimated blood loss of laparoscopic procedures (112.5 +/- 47.8 mL) was significantly lower than that of open surgery. The catheterization time and hospital stay time was significantly shorter than open surgery. The improvement of the International Prostate Symptom Score, maximum flow rate, and quality-of-life score were not different between the comparing groups. Conclusions: The laparoscopic Madigan prostatectomy is a safe and feasible approach for large glands (BPH). Furthermore, its advantages include shorter learning curve, reduced blood loss, less retroejaculation rate, shorter catheterization time, and shorter hospital stay.