Miracle-dz/UniFAR-FTUs huggingface dataset:
DeepSF: deep convolutional neural network for mapping protein sequences to folds

Motivation Protein fold recognition is an important problem in structural bioinformatics. Almost all traditional fold recognition methods use sequence (homology) comparison to indirectly predict the fold of a target protein based on the fold of a template protein with known structure, which cannot explain the relationship between sequence and fold. Only a few methods had been developed to classify protein sequences into a small number of folds due to methodological limitations, which are not generally useful in practice. Results We develop a deep 1D‐convolution neural network (DeepSF) to directly classify any protein sequence into one of 1195 known folds, which is useful for both fold recognition and the study of sequence‐structure relationship. Different from traditional sequence alignment (comparison) based methods, our method automatically extracts fold‐related features from a protein sequence of any length and maps it to the fold space. We train and test our method on the datasets curated from SCOP1.75, yielding an average classification accuracy of 75.3%. On the independent testing dataset curated from SCOP2.06, the classification accuracy is 73.0%. We compare our method with a top profile‐profile alignment method—HHSearch on hard template‐based and template‐free modeling targets of CASP9‐12 in terms of fold recognition accuracy. The accuracy of our method is 12.63‐26.32% higher than HHSearch on template‐free modeling targets and 3.39‐17.09% higher on hard template‐based modeling targets for top 1, 5 and 10 predicted folds. The hidden features extracted from sequence by our method is robust against sequence mutation, insertion, deletion and truncation, and can be used for other protein pattern recognition problems such as protein clustering, comparison and ranking. Availability and implementation The DeepSF server is publicly available at: http://iris.rnet. missouri.edu/DeepSF/. Supplementary information Supplementary data are available at Bioinformatics online.
The Value of MRI in Diagnosis of Solid Pancreatic Tumors

Aim: To investigate the value of 3.0 T MRI in the diagnosis of solid pancreatic tumor. Materials and Methods: Aggregate of 36 patients were enlisted with suspected or proven as solid pancreatic tumors were collected from the first affiliated Hospital of Anhui Medical University Teaching Hospital during the period of January 2012 to August 2015, contained 20 cases of pancreatic adenocarcinoma, 7 cases of pancreatic neuroendocrine tumors (PNETs), 5 cases of pancreatic metastases, 4 cases of solid pseudopapillary tumors (SPTP). All the patients performed with plain scan and multiphasic contrast enhanced imaging on 3.0 T MR, 23 cases performed with MRCP. The data of clinic and imaging were retrospectively analyzed. Results: Pancreatic adenocarcinoma was irregular in shape, lesion was hypo intense in 10 cases, slightly hypo intense in 9 cases and isointense in one case on T1WI. 10 tumor showed slightly enhancement in arterial phase, and all of tumors showed moderate enhancement during portal and delayed phase; 19 cases showed double duct sign, and one case showed distal pancreatic duct dilation. Of the 7 cases with PNETs, the margin was well defined in six well differentiated lesions and ill-defined in one pancreatic neuroendocrine carcinoma; six tumors were marked enhancement in arterial phase and one tumor was moderate enhancement in pancreatic parenchyma in all of three phases. The mean diameter of SPTP was 5.2 cm. The solid part of tumors was hyperintense on T1WI and slightly hyper intense on T2WI, with progressively enhancement. 4 SPTPs had capsule which were hyperintense on T1WI and T2WI exhibited moderate enhancement. Of the 5 pancreatic metastases, one cases had only one lesion, two cases had multiple lesions and two cases showed diffuse pancreatic enlargement, one case showed heterogenous slightly enhancement, two case showed peripheral rim enhancement, two case showed marked enhancement in arterial, then wash-out in delayed and portal phases. Conclusion: MRI is valuable for diagnosis and distinguishing solid pancreatic tumors.
Optimization Strategies for Real-Time Control of an Autonomous Melting Probe

We present an optimization-based approach for trajectory planning and control of a maneuverable melting probe with a high number of binary control variables. The dynamics of the system are modeled by a set of ordinary differential equations with a priori knowledge of system parameters of the melting process. The original planning problem is handled as an optimal control problem. Then, optimal control is used for reference trajectory planning as well as in an MPC-like algorithm. Finally, to determine binary control variables, a MINLP fitting approach is presented. The proposed strategy has recently been tested during experiments on the Langenferner glacier. The data obtained is used for model improvement by means of automated parameter identification.
An Adaptive Strategy for Active Learning with Smooth Decision Boundary

We present the first adaptive strategy for active learning in the setting of classification with smooth decision boundary. The problem of adaptivity (to unknown distributional parameters) has remained opened since the seminal work of Castro and Nowak (2007), which first established (active learning) rates for this setting. While some recent advances on this problem establish adaptive rates in the case of univariate data, adaptivity in the more practical setting of multivariate data has so far remained elusive. Combining insights from various recent works, we show that, for the multivariate case, a careful reduction to univariate-adaptive strategies yield near-optimal rates without prior knowledge of distributional parameters.
Blood Transfusion and Postoperative Infection in Spine Surgery: A Systematic Review

Study Design: Systematic review. Objectives: Allogeneic blood transfusion-related immunomodulation may relatively suppress the immune system, heightening the risk of infection following spine surgery. This systematic review seeks to determine whether allogeneic blood transfusion increases the risk of postoperative infection and whether there are any factors that modify this association. Methods: PubMed, Cochrane Central Register of Controlled Trials, and reference lists from included studies were searched from inception to April 20, 2017 to identify studies examining the risk of infection following allogeneic blood transfusion in adult patients receiving surgery for degenerative spine disease. Results: Eleven retrospective cohort or case-control studies, involving 8428 transfusion patients and 43 242 nontransfusion patients, were identified as meeting the inclusion criteria. Regarding surgical site infection (SSI), the results were mixed with roughly half reporting a significant association. There was an association between allogeneic transfusion and urinary tract infection (UTI) and any infection, but not respiratory tract infection. There was no statistical modifying effect of lumbar versus thoracic surgery on the association of allogeneic transfusion and SSI, though subgroup analyses in 3 of 4 studies reported a statistical association between transfusion and postoperative infections, including SSI, UTI, and any infection within the lumbar spine. Conclusions: This systematic review failed to find a consistent association between allogeneic transfusion and postoperative infection in spine surgery patients. However, these studies were all retrospective with a high or moderately high risk of bias. To properly examine this association an observational prospective study of sufficient power, estimated as 2400 patients, is required.
A Comprehensive Evaluation Method of Node Effectiveness based on Multi-identity and Multi-attribute Decision-making

Existing studies show that the importance evaluation of nodes in complex networks provides theoretical support for the maximization of influence. However, In order to comprehensively evaluate the importance of nodes, the existing node importance research lacks the diversity of index and the difference of node identity which makes the sorting results are more consistent with the actual situation. In this paper, a comprehensive evaluation method of node influence based on a multi-identity and multi-attribute decision-making model is proposed in which each node's multiple evaluation indexes are regarded as the identity attribute of the node, so the importance evaluation of nodes is transformed into a decision problem with multiple identities and multiple attributes. At the same time, through the "kite network" and "micro-blog network" for example analysis, the experimental results show that this method can evaluate the importance of nodes more comprehensively, and has good effectiveness.
Dynamic Mechanism Design in the Field

Dynamic mechanisms are a powerful technique in designing revenue-maximizing repeated auctions. Despite their strength, these types of mechanisms have not been widely adopted in practice for several reasons, e.g., for their complexity, and for their sensitivity to the accuracy of predicting buyers» value distributions. In this paper, we aim to address these shortcomings and develop simple dynamic mechanisms that can be implemented efficiently, and provide theoretical guidelines for decreasing the sensitivity of dynamic mechanisms on prediction accuracy of buyers» value distributions. We prove that the dynamic mechanism we propose is provably dynamic incentive compatible, and introduce a notion of buyers» regret in dynamic mechanisms, and show that our mechanism achieves bounded regret while improving revenue and social welfare compared to a static reserve pricing policy. Finally, we confirm our theoretical analysis via an extensive empirical study of our dynamic auction on real data sets from online adverting. For example, we show our dynamic mechanisms can provide a +17% revenue lift with relative regret less than 0.2%.
Heuristic Approaches for Goal Recognition in Incomplete Domain Models

Recent approaches to goal recognition have progressively relaxed the assumptions about the amount and correctness of domain knowledge and available observations, yielding accurate and efficient algorithms. These approaches, however, assume completeness and correctness of the domain theory against which their algorithms match observations: this is too strong for most real-world domains. In this paper, we develop goal recognition techniques that are capable of recognizing goals using \textit{incomplete} (and possibly incorrect) domain theories. We show the efficiency and accuracy of our approaches empirically against a large dataset of goal and plan recognition problems with incomplete domains.
Recent advances in cannabinoid receptor agonists and antagonists

This review is an overview of the recent advances in cannabinoid chemistry with a special emphasis on the patent literature. The term cannabinoid includes analogues of the natural components of cannabis, endocannabinoids and a wide array of chemical structures such as 1,5-diarylpyrazoles, indoles, quinolines and arylsulphonamide derivatives capable of acting as cannabinoid receptor agonists and antagonists. These receptors, discovered in the early nineties, seem to be involved in different biochemical processes and thus represent interesting therapeutic targets for drug research.
Effect of different irrigations on the bond strength of self-adhesive resin cement to root dentin

Background Different disinfectant solutions or medications are indicated prior fiber post bonding procedures.The aim was to evaluate the effect of different pretreatments of root canal on the bond strength of a fiber post luted to dentin with self-adhesive resin cement. Material and Methods Forty-eight single-rooted mandibular premolars were endodontically treated and prepared to receive fiber posts. Teeth were assigned to four groups (n=12). Root canal walls were subjected to no pretreatment (G1 - control); irrigation with 10 mL of 5% sodium hypochlorite (NaOCl) (G2); 10 mL of 17% ethylenediaminetetraacetic acid (EDTA) associated with 10 mL of 5% NaOCl (G3); or 10 mL of 17% EDTA (G4). Fiber posts were bonded with self-adhesive cement. After the roots were sectioned into slices, a push-out bond strength test was performed using a universal testing machine at crosshead speed of 0.5 mm/min. Bond strength data were recorded and expressed in MPa and analyzed by Anova (5%) and Tukey Test (5%). Results It was found that G2 (9.36 MPa) and G4 (6.33 MPa) were significantly different among themselves and statistically inferior to G1 (13.93 MPa) while G3 (14.31 MPa) was statistically similar to G1 (control) and superior to G2 and G4. Conclusions Irrigation with 17% EDTA associated with 5% NaOCl showed increased bond strength compared with the same solutions used alone. Key words:Self-adhesive, Dentin, Push-out, Bonding.
Psychosocial distress and the preferred method of delivery of mind–body interventions among patients with head-and-neck cancer

Objective To describe the psychosocial distress of head-and-neck cancer patients at the completion of therapy and the interest in and the preferred method of delivery of mind–body interventions (MBIs) among head-and-neck cancer patients. Materials and methods A descriptive, cross-sectional design was used to measure sleep disturbance, depression, anxiety, and the interest in and the preference for MBIs using anonymous, self-report questionnaires among a convenience sample of 30 males at their 3-month follow-up. Questionnaires included the Pittsburgh Sleep Quality Index, Hospital Anxiety and Depression Scale, and the self-created Survey for Preferred Methods of MBI. Frequency distributions and descriptive statistics were used to describe the sample demographic and clinical characteristics. Results The mean age of the sample was 59 years. Oral cancer (63%) was the most common type of cancer. Nineteen participants (63%, 90% CI 47%–78%) had some interest in MBIs. Of interested participants, 8 (42%) preferred participating in MBIs alone, 10 (53%) preferred participating in MBIs at homes, 10 (53%) preferred participating in MBIs using a computer or mobile device, and 8 (42%) preferred participating in MBIs after the diagnosis, but before treatment started. Mean depression, anxiety, and sleep disturbance scores were 8.25 (SD 2.93), 5.41 (SD 3.52), and 6.3 (SD 3.86), respectively. Results from the independent-samples t-test and Mann–Whitney U tests revealed no significant differences in anxiety, depression, and sleep disturbance by MBI interest. Conclusion Asking about depression, anxiety, and sleep disturbances may help to identify head-and-neck cancer patients at risk for psychosocial distress. These findings suggest an interest in MBIs, but further research is warranted.
Direct Experimental Characterization of Glycosyl Cations by Infrared Ion Spectroscopy

Glycosyl cations are crucial intermediates formed during enzymatic and chemical glycosylation. The intrinsic high reactivity and short lifetime of these reaction intermediates make them very challenging to characterize using spectroscopic techniques. Herein, we report the use of collision induced dissociation tandem mass spectrometry to generate glycosyl cations in the gas phase followed by infrared ion spectroscopy using the FELIX infrared free electron laser. The experimentally observed IR spectra were compared to DFT calculated spectra enabling the detailed structural elucidation of elusive glycosyl oxocarbenium and dioxolenium ions.
Minimax Reconstruction Risk of Convolutional Sparse Dictionary Learning

Sparse dictionary learning (SDL) has become a popular method for learning parsimonious representations of data, a fundamental problem in machine learning and signal processing. While most work on SDL assumes a training dataset of independent and identically distributed (IID) samples, a variant known as convolutional sparse dictionary learning (CSDL) relaxes this assumption to allowdependent, non-stationary sequential data sources. Recent work has explored statistical properties of IID SDL; however, the statistical properties of CSDL remain largely unstudied. This paper identifies minimax rates of CSDL in terms of reconstruction risk, providing both lower and upper bounds in a variety of settings. Our results make minimal assumptions, allowing arbitrary dictionaries and showing that CSDL is robust to dependent noise. We compare our results to similar results for IID SDL and verify our theory with synthetic experiments.
A PAIR OF INERTIAL FRAMES VERSUS AN INERTIAL FRAME

Without an inertial frame, we are unable to identify and define the force(s) acting upon an object. Without force, we are unable to classify and define an inertial frame(s) to describe the motion of objects. Because the circular definitions of inertia and force, we propose to remove the dynamic aspect of the definition and employ only kinetics in defining what an inertial frame is. Kinetically, we are unable to define an inertial frame, but we can define a pair of inertial frames: a pair of reference frames which have a constant relative velocity with respect to each other. There are infinitely many pairs of inertial frames in the universe, which can be dierentiated into separate groups. If a new pair of inertial frames can be formed from an existing pair of inertial frames, then these inertial frames all belong to the same pair-group. The Principle
Isolation of Extracellular Vesicles: General Methodologies and Latest Trends

Background Extracellular vesicles (EVs) play an essential role in the communication between cells and transport of diagnostically significant molecules. A wide diversity of approaches utilizing different biochemical properties of EVs and a lack of accepted protocols make data interpretation very challenging. Scope of Review This review consolidates the data on the classical and state-of-the-art methods for isolation of EVs, including exosomes, highlighting the advantages and disadvantages of each method. Various characteristics of individual methods, including isolation efficiency, EV yield, properties of isolated EVs, and labor consumption are compared. Major Conclusions A mixed population of vesicles is obtained in most studies of EVs for all used isolation methods. The properties of an analyzed sample should be taken into account when planning an experiment aimed at studying and using these vesicles. The problem of adequate EVs isolation methods still remains; it might not be possible to develop a universal EV isolation method but the available protocols can be used towards solving particular types of problems. General Significance With the wide use of EVs for diagnosis and therapy of various diseases the evaluation of existing methods for EV isolation is one of the key problems in modern biology and medicine.
Impact of mHealth Chronic Disease Management on Treatment Adherence and Patient Outcomes: A Systematic Review

Background Adherence to chronic disease management is critical to achieving improved health outcomes, quality of life, and cost-effective health care. As the burden of chronic diseases continues to grow globally, so does the impact of non-adherence. Mobile technologies are increasingly being used in health care and public health practice (mHealth) for patient communication, monitoring, and education, and to facilitate adherence to chronic diseases management. Objective We conducted a systematic review of the literature to evaluate the effectiveness of mHealth in supporting the adherence of patients to chronic diseases management (“mAdherence”), and the usability, feasibility, and acceptability of mAdherence tools and platforms in chronic disease management among patients and health care providers. Methods We searched PubMed, Embase, and EBSCO databases for studies that assessed the role of mAdherence in chronic disease management of diabetes mellitus, cardiovascular disease, and chronic lung diseases from 1980 through May 2014. Outcomes of interest included effect of mHealth on patient adherence to chronic diseases management, disease-specific clinical outcomes after intervention, and the usability, feasibility, and acceptability of mAdherence tools and platforms in chronic disease management among target end-users. Results In all, 107 articles met all inclusion criteria. Short message service was the most commonly used mAdherence tool in 40.2% (43/107) of studies. Usability, feasibility, and acceptability or patient preferences for mAdherence interventions were assessed in 57.9% (62/107) of studies and found to be generally high. A total of 27 studies employed randomized controlled trial (RCT) methods to assess impact on adherence behaviors, and significant improvements were observed in 15 of those studies (56%). Of the 41 RCTs that measured effects on disease-specific clinical outcomes, significant improvements between groups were reported in 16 studies (39%). Conclusions There is potential for mHealth tools to better facilitate adherence to chronic disease management, but the evidence supporting its current effectiveness is mixed. Further research should focus on understanding and improving how mHealth tools can overcome specific barriers to adherence.
An Automated Approach to Auditing Disclosure of Third-Party Data Collection in Website Privacy Policies

A dominant regulatory model for web privacy is "notice and choice". In this model, users are notified of data collection and provided with options to control it. To examine the efficacy of this approach, this study presents the first large-scale audit of disclosure of third-party data collection in website privacy policies. Data flows on one million websites are analyzed and over 200,000 websites' privacy policies are audited to determine if users are notified of the names of the companies which collect their data. Policies from 25 prominent third-party data collectors are also examined to provide deeper insights into the totality of the policy environment. Policies are additionally audited to determine if the choice expressed by the "Do Not Track" browser setting is respected. Third-party data collection is wide-spread, but fewer than 15% of attributed data flows are disclosed. The third-parties most likely to be disclosed are those with consumer services users may be aware of, those without consumer services are less likely to be mentioned. Policies are difficult to understand and the average time requirement to read both a given site»s policy and the associated third-party policies exceeds 84 minutes. Only 7% of first-party site policies mention the Do Not Track signal, and the majority of such mentions are to specify that the signal is ignored. Among third-party policies examined, none offer unqualified support for the Do Not Track signal. Findings indicate that current implementations of "notice and choice" fail to provide notice or respect choice.