Miracle-dz/UniFAR-FTUs huggingface dataset:
A new authentication protocol for healthcare applications using wireless medical sensor networks with user anonymity

With the development and maturation of the wireless communication technologies, the wireless sensor networks have been widely applied in different environments to acquire specific information. The wireless medical sensor networks WMSNs, as a professional application of the wireless sensor networks in medicine, have attracted more and more attention because of its potential in improving the quality of healthcare services. Through the WMSNs, the parameters of patients' vital signs can be gathered from the sensor nodes equipped on the body of the patients and then can be accessed by the healthcare professionals by using a mobile device. By reason of the open feature of wireless communication, how to guarantee secure communication becomes an important issue. On the other hand, because the vital signs parameters are sensitive to the patients' health status and no one wants to reveal it to the others except the healthcare professionals, the protection of patients' privacy becomes another key issue for WMSNs applications. User authentication protocol with anonymity is the most basic and commonly used method to resolve the security and privacy issues of WMSNs. Recently, He et al. proposed an enhanced authentication protocol for healthcare applications using WMSNs to protect the security and privacy problems. However, we find that their scheme is incorrect in authentication and session key agreement phase. Besides, their scheme has no wrong password detection mechanism, which will not only waste the unnecessary computation and communication costs, but also may deduce the denial of service problem. In this paper, the biometric is introduced as the third authentication factor, and a new user anonymous authentication protocol based on WMSNs is designed so as to remove the drawbacks of the protocol of He et al. Compared with previous protocols, the new presented protocol enhances the security and also keeps the computation efficiency. Copyright © 2015John Wiley & Sons, Ltd.
Comparing Simultaneous Liver-Kidney Transplant Strategies: A Modified Cost-Effectiveness Analysis

Background The proportion of patients with kidney failure at time of liver transplantation is at a historic high in the United States. The optimal timing of kidney transplantation with respect to the liver transplant is unknown. Methods We used a modified cost-effectiveness analysis to compare 4 strategies: the old system (“pre-OPTN”), the new Organ Procurement Transplant Network (OPTN) system since August 10, 2017 (“OPTN”), and 2 strategies which restrict simultaneous liver-kidney transplants (“safety net” and “stringent”). We measured “cost” by deployment of deceased donor kidneys (DDKs) to liver transplant recipients and effectiveness by life years (LYs) and quality-adjusted life years (QALYs) in liver transplant recipients. We validated our model against Scientific Registry for Transplant Recipients data. Results The OPTN, safety net and stringent strategies were on the efficiency frontier. By rank order, OPTN > safety net > stringent strategy in terms of LY, QALY, and DDK deployment. The pre-OPTN system was dominated, or outperformed, by all alternative strategies. The incremental LY per DDK between the strategies ranged from 1.30 to 1.85. The incremental QALY per DDK ranged from 1.11 to 2.03. Conclusions These estimates quantify the “organ”-effectiveness of various kidney allocation strategies for liver transplant candidates. The OPTN system will likely deliver better liver transplant outcomes at the expense of more frequent deployment of DDKs to liver transplant recipients.
Novel Unsupervised Classification of Collapsed Buildings Using Satellite Imagery, Hazard Scenarios and Fragility Functions

Although supervised machine learning classification techniques have been successfully applied to detect collapsed buildings, there is still a major problem that few publications have addressed. The success of supervised machine learning strongly depends on the availability of training samples. Unfortunately, in the aftermath of a large-scale disaster, training samples become available only after several weeks or even months. However, following a disaster, information on the damage situation is one of the most important necessities for rapid search-and-rescue efforts and relief distribution. In this paper, a modification of the supervised machine learning classification technique called logistic regression is presented. Here, the training samples are replaced with probabilistic information, which is calculated from the spatial distribution of the hazard under consideration and one or more fragility functions. Such damage probabilities can be collected almost in real time for specific disasters such as earthquakes and/or tsunamis. We present the application of the proposed method to the 2011 Great East Japan Earthquake and Tsunami for collapsed building detection. The results show good agreement with a field survey performed by the Ministry of Land, Infrastructure, Transport and Tourism, with an overall accuracy of over 80%. Thus, the proposed method can significantly contribute to a rapid estimation of the number and locations of collapsed buildings.
Evaluation of a Web-Based Training in Smoking Cessation Counseling Targeting U.S. Eye-Care Professionals

Background. Smoking causes blindness-related diseases. Eye-care providers are uniquely positioned to help their patients quit smoking. Aims. Using a pre-/postevaluation design, this study evaluated a web-based training in smoking cessation counseling targeting eye-care providers. Method. The training was developed based on the 3A1R protocol: “Ask about smoking, Advise to quit, Assess willingness to quit, and Refer to tobacco quitlines,” and made available in the form of a web-based video presentation. Providers (n = 654) at four academic centers were invited to participate. Participants completed pretraining, posttraining, and 3-month follow-up surveys. Main outcomes were self-reported improvement in their motivation, confidence, and counseling practices at 3-month follow-up. Generalized linear mixed models for two time-points (pretraining and 3-month) were conducted for these outcomes. Results. A total of 113 providers (54.0% males) participated in the study (17.7% response rate). At the 3-month evaluation, 9.8% of participants reported improvement in their motivation. With respect to the 3A1R, 8% reported improvement in their confidence for Ask, 15.5% for Advise, 28.6% for Assess, and 37.8% for Refer. Similarly, 25.5% reported improvement in their practices for Ask, 25.5% for Advise, 37.2% for Assess, and 39.4% for Refer to tobacco quitlines (p < .001 for all except for Refer confidence p = .05). Discussion. Although participation rate was low, the program effectively improved providers’ smoking cessation counseling practices. Conclusions. Including training in smoking cessation counseling in ophthalmology curriculums, and integrating the 3A1R protocol into the electronic medical records systems in eye-care settings, might promote smoking cessation practices in these settings.
Novel stability criteria for bidirectional associative memory neural networks with time delays

In this paper, the bidirectional associative memory (BAM) neural network with axonal signal transmission delay is considered. This model is also referred to as a delayed dynamic BAM model. By combining a number of different Lyapunov functionals with the Razumikhin technique, some sufficient conditions for the existence of a unique equilibrium and global asymptotic stability of the network are derived. These results are fairly general and can be easily verified. Besides, the approach for the analysis allows one to consider several different types of activation functions, including piecewise linear sigmoids with bounded activations as well as C1‐smooth sigmoids. It is believed that these results are significant and convenient in the design and applications of BAM neural networks. Copyright © 2002 John Wiley & Sons, Ltd.
FastDeRain: A Novel Video Rain Streak Removal Method Using Directional Gradient Priors

Rain streaks removal is an important issue in outdoor vision systems and has recently been investigated extensively. In this paper, we propose a novel video rain streak removal approach FastDeRain, which fully considers the discriminative characteristics of rain streaks and the clean video in the gradient domain. Specifically, on the one hand, rain streaks are sparse and smooth along the direction of the raindrops, whereas on the other hand, clean videos exhibit piecewise smoothness along the rain-perpendicular direction and continuity along the temporal direction. Theses smoothness and continuity result in the sparse distribution in the different directional gradient domain. Thus, we minimize: 1) the <inline-formula> <tex-math notation="LaTeX">$\ell _{1}$ </tex-math></inline-formula> norm to enhance the sparsity of the underlying rain streaks; 2) two <inline-formula> <tex-math notation="LaTeX">$\ell _{1}$ </tex-math></inline-formula> norm of unidirectional total variation regularizers to guarantee the anisotropic spatial smoothness; and 3) an <inline-formula> <tex-math notation="LaTeX">$\ell _{1}$ </tex-math></inline-formula> norm of the time-directional difference operator to characterize the temporal continuity. A split augmented Lagrangian shrinkage algorithm-based algorithm is designed to solve the proposed minimization model. Experiments conducted on synthetic and real data demonstrate the effectiveness and efficiency of the proposed method. According to the comprehensive quantitative performance measures, our approach outperforms other state-of-the-art methods, especially on account of the running time. The code of FastDeRain can be downloaded at <uri>https://github.com/TaiXiangJiang/FastDeRain</uri>.
Comparison of protein-based cell-of-origin classification to the Lymph2Cx RNA assay in a cohort of diffuse large B-cell lymphomas in Malaysia

Aims The cell of origin (COO) based molecular characterisation into germinal centre B-cell-like (GCB) and activated B-cell-like (ABC) subtypes are central to the pathogenesis and clinical course in diffuse large B-cell lymphoma (DLBCL). Globally, clinical laboratories employ pragmatic but less than ideal immunohistochemical (IHC) assay for COO classification. Novel RNA-based platforms using routine pathology samples are emerging as new gold standard and offer unique opportunities for assay standardisation for laboratories across the world. We evaluated our IHC protocols against RNA-based technologies to determine concordance; additionally, we gauged the impact of preanalytical variation on the performance of Lymph2Cx assay. Methods Diagnostic biopsies (n=104) were examined for COO classification, employing automated RNA digital quantification assay (Lymph2Cx). Results were equated against IHC-based COO categorisation. Assay performance was assessed through its impact on overall survival (OS). Results 96 (92%) informative samples were labelled as GCB (38/96; 40%) and non-GCB (58/96; 60%) by IHC evaluation. Lymph2Cx catalogued 36/96 (37%) samples as GCB, 45/96 (47%) as ABC and 15/96 (16%) as unclassified. Lymph2Cx being reference, IHC protocol revealed sensitivity of 81% for ABC and 75% for GCB categorisation and positive predictive value of 81% versus 82%, respectively. Lymph2Cx-based COO classification performed superior to Hans algorithm in predicting OS (log rank test, p=0.017 vs p=0.212). Conclusions Our report show that current IHC-based protocols for COO classification of DLBCL at UKM Malaysia are in line with previously reported results and marked variation in preanalytical factors do not critically impact Lymph2Cx assay quality.
University of Birmingham Identification of Tspan9 as a novel platelet tetraspanin and the collagen receptor GPVI as a component of tetraspanin microdomains

Citation for published version (Harvard): Protty, M, Watkins, N, Colombo, D, Thomas, S, Heath, V, Herbert, J, Bicknell, R, Senis, Y, Ashman, L, Berditchevski, F, Ouwehand, W, Watson, S & Tomlinson, M 2009, 'Identification of Tspan9 as a novel platelet tetraspanin and the collagen receptor GPVI as a component of tetraspanin microdomains', Biochemical Journal, vol. 417, no. 1, pp. 391-. https://doi.org/10.1042/BJ20081126
Meta Reinforcement Learning with Latent Variable Gaussian Processes

Learning from small data sets is critical in many practical applications where data collection is time consuming or expensive, e.g., robotics, animal experiments or drug design. Meta learning is one way to increase the data efficiency of learning algorithms by generalizing learned concepts from a set of training tasks to unseen, but related, tasks. Often, this relationship between tasks is hard coded or relies in some other way on human expertise. In this paper, we frame meta learning as a hierarchical latent variable model and infer the relationship between tasks automatically from data. We apply our framework in a model-based reinforcement learning setting and show that our meta-learning model effectively generalizes to novel tasks by identifying how new tasks relate to prior ones from minimal data. This results in up to a 60% reduction in the average interaction time needed to solve tasks compared to strong baselines.
Depression among Chinese University Students: Prevalence and Socio-Demographic Correlates

The purpose of the present study was to estimate the prevalence of depression in Chinese university students, and to identify the socio-demographic factors associated with depression in this population. A multi-stage stratified sampling procedure was used to select university students (N = 5245) in Harbin (Heilongjiang Province, Northeastern China), who were aged 16–35 years. The Beck Depression Inventory (BDI) was used to determine depressive symptoms of the participants. BDI scores of 14 or higher were categorized as depressive for logistic regression analysis. Depression was diagnosed by the Structured Clinical Interview (SCID) for the Diagnostic and Statistical Manual of Mental Disorders-Fourth Edition (DSM-IV). 11.7% of the participants had a BDI score 14 or higher. Major Depressive Disorder was seen in 4.0% of Chinese university students. There were no statistical differences in the incidence of depression when gender, ethnicity, and university classification were analyzed. Multivariate analysis showed that age, study year, satisfaction with major, family income situation, parental relationship and mother's education were significantly associated with depression. Moderate depression is prevalent in Chinese university students. The students who were older, dissatisfied with their major, had a lower family income, poor parental relationships, and a lower level of mother's education were susceptible to depression.
Sparse Word Embeddings Using ℓ1 Regularized Online Learning

Recently, Word2Vec tool has attracted a lot of interest for its promising performances in a variety of natural language processing (NLP) tasks. However, a critical issue is that the dense word representations learned in Word2Vec are lacking of interpretability. It is natural to ask if one could improve their interpretability while keeping their performances. Inspired by the success of sparse models in enhancing interpretability, we propose to introduce sparse constraint into Word2Vec. Specifically, we take the Continuous Bag of Words (CBOW) model as an example in our study and add the ll regularizer into its learning objective. One challenge of optimization lies in that stochastic gradient descent (SGD) cannot directly produce sparse solutions with l1 regularizer in online training. To solve this problem, we employ the Regularized Dual Averaging (RDA) method, an online optimization algorithm for regularized stochastic learning. In this way, the learning process is very efficient and our model can scale up to very large corpus to derive sparse word representations. The proposed model is evaluated on both expressive power and interpretability. The results show that, compared with the original CBOW model, the proposed model can obtain state-of-the-art results with better interpretability using less than 10% non-zero elements.
Determinants of Role Structure in Family Financial Management

Variables determining the role of husband and wife in family financial management are explored based on in-home, personal interviews. Financial tasks reflecting implementation activities and two groupings of decision activities were related to component-score variables through discriminant function analysis. Sex-role attitude and educational level were most important in determining the role structure of implementation tasks. Locus of control, wife's working status and reasons for work, and a measure of family life cycle were each significant in determining role structure for a grouping of decision tasks.
Comparison of the success rate between monocanalicular and bicanalicular intubations in incomplete complex congenital nasolacrimal duct obstruction

ABSTRACT This article compares the success rate between monocanalicular (MCI) and bicanalicular intubations (BCI) in incomplete complex congenital nasolacrimal duct obstruction (CNLDO) and evaluate the factors responsible for the success of intubation. First, 99 patients with incomplete complex CNLDO underwent MCI (Monoka) or BCI (Crawford). Therapeutic success was defined as dye disappearance test grade 0-1 and complete resolution of previous symptoms at 12 months’ follow-up. The success rates were compared between two groups. In all cases, the correlation of the age, gender, history of probing, and the presence of purulent discharges with the improvement in CNLDO symptoms were evaluated. 52 cases in the MCI and 47 cases in the BCI group were included. Then, 48 patients (48.5%) had history of probing. 26 patients (26.3%) had purulent discharges. The patients in the MCI group had lower success rate (59.6%) than the patients in the BCI group (74.4%) but the difference was not significant (p = 0.11). No complication occurred in the BCI group. In 4 cases (7.6%) in the MCI group, the tubes were lost before time of planned removal. In all cases, only preoperative absence of the pus was significantly correlated with success (p = 0.09 and OR = 0.39). BCI may be a better treatment for the patients with incomplete complex CNLDO. In silicone intubation for these cases, preoperative absence of purulent discharges could increase the success rate.
HARP: Hierarchical Representation Learning for Networks

We present HARP, a novel method for learning low dimensional embeddings of a graph’s nodes which preserves higher-order structural features. Our proposed method achieves this by compressing the input graph prior to embedding it, effectively avoiding troublesome embedding configurations (i.e. local minima) which can pose problems to non-convex optimization. HARP works by finding a smaller graph which approximates the global structure of its input. This simplified graph is used to learn a set of initial representations, which serve as good initializations for learning representations in the original, detailed graph. We inductively extend this idea, by decomposing a graph in a series of levels, and then embed the hierarchy of graphs from the coarsest one to the original graph. HARP is a general meta-strategy to improve all of the state-of-the-art neural algorithms for embedding graphs, including DeepWalk, LINE, and Node2vec. Indeed, we demonstrate that applying HARP’s hierarchical paradigm yields improved implementations for all three of these methods, as evaluated on classification tasks on real-world graphs such as DBLP, BlogCatalog, and CiteSeer, where we achieve a performance gain over the original implementations by up to 14% Macro F1.
Recovery of inulin from Jerusalem artichoke (Helianthus tuberosus L.) in the small intestine of man

The recovery of inulin, a naturally occurring β(2→l)-fructan isolated from Jerusalem artichoke (Helianthus tuberosus L.), in the small intestine of man was studied in ileostomy subjects. The ileostomists were given a low-dietary-fibre diet based on white wheat bread and virtually free of inulin, and the same diet with the addition of 10 g and 30 g inulin product respectively, and the recovery and mean transit time (MTT) of inulin were estimated by tracking inulin in ileal effluent. The recovery of inulin was approximately 87% at both ingestion levels. MTT was 4·9 (SE 0·6) h at an intake of 10 g inulin product decreasing to 3·4 (SE 0·3) h at an intake of 30 g Inulin product. A significant change in the fructose: glucose ratio of inulin from ingestion (4·1) to recovery in ileal effluent (4·5–4·7) and a lower recovery of the glucose residue than of the fructose residue of inulin indicate that the low-molecular-weight inulins are more sensitive to hydrolysis than the high-molecular-weight fragments. The loss of inulin during passage through the small intestine is presumably due to hydrolysis by either acids or enzymes and to microbial degradation by the microfiora permanently colonizing the distal small intestine. The concentrations of lactic acid (LA) and short-chain fatty acids (SCFA) in frequently collected ileal effluents on the control day were approximately 6 mmol/l and approximately 55 mmol/l respectively. During periods with inulin ingestion the concentration of LA increased to 18–26 mmol/l (P < 0·052), while the concentration of SCFA ran converse and decreased to 18–32 mmol/l (P < 0·023). The osmotic loads (68 and 204 mosmol/l) associated with the ingestion of inulin product caused minor malabsorption of low-molecular-weight sugars.
Outer nuclear membrane protein Kuduk modulates the LINC complex and nuclear envelope architecture

Linker of nucleoskeleton and cytoskeleton (LINC) complexes spanning the nuclear envelope (NE) contribute to nucleocytoskeletal force transduction. A few NE proteins have been found to regulate the LINC complex. In this study, we identify one, Kuduk (Kud), which can reside at the outer nuclear membrane and is required for the development of Drosophila melanogaster ovarian follicles and NE morphology of myonuclei. Kud associates with LINC complex components in an evolutionarily conserved manner. Loss of Kud increases the level but impairs functioning of the LINC complex. Overexpression of Kud suppresses NE targeting of cytoskeleton-free LINC complexes. Thus, Kud acts as a quality control mechanism for LINC-mediated nucleocytoskeletal connections. Genetic data indicate that Kud also functions independently of the LINC complex. Overexpression of the human orthologue TMEM258 in Drosophila proved functional conservation. These findings expand our understanding of the regulation of LINC complexes and NE architecture.
Knockout of Murine Mamld1 Impairs Testicular Growth and Daily Sperm Production but Permits Normal Postnatal Androgen Production and Fertility

MAMLD1 has been implicated in testicular function in both human and mouse fetuses. Although three patients with MAMLD1 mutations were reported to have hypergonadotropic hypogonadism in their teens, the functional significance of MAMLD1 in the postnatal testis remains unclear. Here, we analyzed the phenotype of Mamld1 knockout (KO) male mice at reproductive ages. The reproductive organs of KO male mice were morphologically unremarkable, except for relatively small testes. Seminiferous tubule size and number of proliferating spermatogonia/spermatocytes were reduced in the KO testis. Daily sperm production of KO mice was mildly attenuated, whereas total sperm counts in epididymal semen remained normal. Sperm motility and morphology, as well as androgen levels in serum and testicular tissues and the number of pups born from cross-mated wildtype (WT) female mice, were comparable between WT and KO male mice. These results indicate that MAMLD1 contributes to the maintenance of postnatal testicular growth and daily sperm production but is dispensable for androgen biosynthesis and fertility. MAMLD1 likely plays supporting roles in multiple and continuous steps of male reproduction.