Miracle-dz/UniFAR-FTUs huggingface dataset:
Rapid prototyping for patient-specific surgical orthopaedics guides: A systematic literature review

There has been a lot of hype surrounding the advantages to be gained from rapid prototyping processes in a number of fields, including medicine. Our literature review aims objectively to assess how effective patient-specific surgical guides manufactured using rapid prototyping are in a number of orthopaedic surgical applications. To this end, we carried out a systematic review to identify and analyse clinical and experimental literature studies in which rapid prototyping patient-specific surgical guides are used, focusing especially on those that entail quantifiable outcomes and, at the same time, providing details on the guides’ design and type of manufacturing process. Here, it should be mentioned that in this field there are not yet medium- or long-term data, and no information on revisions. In the reviewed studies, the reported positive opinions on the use of rapid prototyping patient-specific surgical guides relate to the following main advantages: reduction in operating times, low costs and improvements in the accuracy of surgical interventions thanks to guides’ personalisation. However, disadvantages and sources of errors which can cause patient-specific surgical guide failures are as well discussed by authors. Stereolithography is the main rapid prototyping process employed in these applications although fused deposition modelling or selective laser sintering processes can also satisfy the requirements of these applications in terms of material properties, manufacturing accuracy and construction time. Another of our findings was that individualised drill guides for spinal surgery are currently the favourite candidates for manufacture using rapid prototyping. Other emerging applications relate to complex orthopaedic surgery of the extremities: the forearm and foot. Several procedures such as osteotomies for radius malunions or tarsal coalition could become standard, thanks to the significant assistance provided by rapid prototyping patient-specific surgical guides in planning and performing such operations.
Two-photon 3D mapping of tisssue endogenous fluorescence species based on fluorescence emission spectra

Two-photon microscopy imaging of endogenous fluorescence has been shown to be a powerful method for the quantification of tissue structure and biochemistry. While autofluorescence is observed in many tissue types, the identities and distributions of these fluorophores have not been completely characterized. Image guided spectral analysis is being developed to aid in extracting spectroscopic components from two-photon images. This methodology is being applied to the study of human skin. In ex vivo specimens, the overall bulk emission spectrum of the skin, the layer-resolved emission spectra of the stratum corneum, stratum spinosum, basal layer, and dermis, and the emission spectra of surgically exposed dermis have been measured. From the image guided spectral analysis, it was determined that there are approximately five factors that contribute to most of the luminescence signals from human skin. The autofluorescent species identified include tryptophan, NAD(P)H, melanin (or localizing species), and elastin. The collagen matrix contributes to a second harmonic signal.
Similarity Learning via Adaptive Regression and Its Application to Image Retrieval

We study the problem of similarity learning and its application to image retrieval with large-scale data. The similarity between pairs of images can be measured by the distances between their high dimensional representations, and the problem of learning the appropriate similarity is often addressed by distance metric learning. However, distance metric learning requires the learned metric to be a PSD matrix, which is computational expensive and not necessary for retrieval ranking problem. On the other hand, the bilinear model is shown to be more flexible for large-scale image retrieval task, hence, we adopt it to learn a matrix for estimating pairwise similarities under the regression framework. By adaptively updating the target matrix in regression, we can mimic the hinge loss, which is more appropriate for similarity learning problem. Although the regression problem can have the closed-form solution, the computational cost can be very expensive. The computational challenges come from two aspects: the number of images can be very large and image features have high dimensionality. We address the first challenge by compressing the data by a randomized algorithm with the theoretical guarantee. For the high dimensional issue, we address it by taking low rank assumption and applying alternating method to obtain the partial matrix, which has a global optimal solution. Empirical studies on real world image datasets (i.e., Caltech and ImageNet) demonstrate the effectiveness and efficiency of the proposed method.
Isolation, identification, and quantification of lichenysin, a novel nonvolatile compound in Chinese distilled spirits.

UNLABELLED Nonvolatile components influence overall flavor volatility and perception in alcoholic beverages. However, little information has been reported about the nonvolatile compounds in Chinese distilled spirits. For the first time, we isolated and identified a cyclic lipopeptide "lichenysin" as a novel nonvolatile compound in Chinese liquors, using preparative high performance liquid chromatography coupled with quadrupole-time-of-flight mass spectrometer and nuclear magnetic resonance. The concentrations of lichenysin were quantified in 14 main types of bottled Chinese liquors by using ultra performance liquid chromatography coupled with triple quadrupole mass spectrometer. The concentrations of lichenysin in Chinese liquor ranged from 0.01 to 111.74 μg/L, where the concentration was the highest in Dongjiu liquor. Furthermore, we found that lichenysin selectively affected aroma volatility in the Chinese liquor, using the headspace solid-phase microextraction coupled with gas chromatography-mass spectrometry. The headspace concentrations of 2-phenylethanol, phenol, and 4-methylphenol significantly decreased by respectively 58%, 76%, and 59% in 3 Chinese commercial liquors with an increase in lichenysin. These results indicated that lichenysin could be a novel nonvolatile compound that selectively affected aroma volatility in Chinese liquors. PRACTICAL APPLICATION This was the first report that lichenysin was isolated, identified, and quantified as a nonvolatile compound in traditional Chinese liquors. Lichenysin selectively affected the volatility of the aroma compounds in Chinese liquors. So far, there is no report on lichenysin in other alcoholic beverages. It would give a new insight into flavoromics in food and help to improve aroma quality of Chinese liquors.
Limits on Efficient Computation in the Physical World

More than a speculative technology, quantum computing seems to challenge our most basic intuitions about how the physical world should behave. In this thesis I show that, while some intuitions from classical computer science must be jettisoned in the light of modern physics, many others emerge nearly unscathed; and I use powerful tools from computational complexity theory to help determine which are which. In the first part of the thesis, I attack the common belief that quantum computing resembles classical exponential parallelism, by showing that quantum computers would face serious limitations on a wider range of problems than was previously known. In particular, any quantum algorithm that solves the collision problem—that of deciding whether a sequence of n integers is one-to-one or two-to-one—must query the sequence Ω (n1/5) times. This resolves a question that was open for years; previously no lower bound better than constant was known. A corollary is that there is no “black-box” quantum algorithm to break cryptographic hash functions or solve the Graph Isomorphism problem in polynomial time. I also show that relative to an oracle, quantum computers could not solve NP-complete problems in polynomial time, even with the help of nonuniform “quantum advice states”; and that any quantum algorithm needs Ω (2n/4/n) queries to find a local minimum of a black-box function on the n-dimensional hypercube. Surprisingly, the latter result also leads to new classical lower bounds for the local search problem. Finally, I give new lower bounds on quantum one-way communication complexity, and on the quantum query complexity of total Boolean functions and recursive Fourier sampling. The second part of the thesis studies the relationship of the quantum computing model to physical reality. I first examine the arguments of Leonid Levin, Stephen Wolfram, and others who believe quantum computing to be fundamentally impossible. I find their arguments unconvincing without a “Sure/Shor separator”—a criterion that separates the already-verified quantum states from those that appear in Shor's factoring algorithm. I argue that such a separator should be based on a complexity classification of quantum states, and go on to create such a classification. Next I ask what happens to the quantum computing model if we take into account that the speed of light is finite—and in particular, whether Grover's algorithm still yields a quadratic speedup for searching a database. Refuting a claim by Benioff, I show that the surprising answer is yes. Finally, I analyze hypothetical models of computation that go even beyond quantum computing. I show that many such models would be as powerful as the complexity class PP, and use this fact to give a simple, quantum computing based proof that PP is closed under intersection. On the other hand, I also present one model—wherein we could sample the entire history of a hidden variable—that appears to be more powerful than standard quantum computing, but only slightly so.
Retrospective evaluation of combined mycophenolate mofetil and prednisone treatment for meningoencephalomyelitis of unknown etiology in dogs: 25 cases (2005-2011).

OBJECTIVE To evaluate the use of a combined protocol of prednisone and mycophenolate mofetil (MMF) for the treatment of meningoencephalomyelitis of unknown etiology (MUE) and to describe response, adverse effects, and outcome. DESIGN Retrospective study (2005-2011). SETTING University teaching hospital. ANIMALS Twenty-five client-owned dogs with clinical signs, neuroimaging, and cerebrospinal abnormalities consistent with MUE. Five dogs whose MMF treatment was discontinued after 7-14 days due to gastrointestinal clinical signs were evaluated only for adverse effects. INTERVENTIONS Dogs were initially treated with prednisone 2 mg/kg PO every 12 hours and with MMF 20 mg/kg PO or IV every 12 hours. Prednisone was tapered after 4 days to 1 mg/kg every 12 hours for 14 days, then to every 24 hours for 30 days, and again reduced by half every 2-4 months thereafter. When prednisone was tapered completely or to 0.5 mg/kg every 24-48 hours without clinical relapse, MMF was tapered in a similar manner. MEASUREMENTS AND MAIN RESULTS Partial or complete clinical response was achieved in 95% (19/20) of the dogs. Median survival time by the end of the study was 250 days (range 6 to >1,679) with 40% (8/20) of the dogs still alive (336-1,679 days after diagnosis). All Pug dogs (4/20) included in the study died with a median survival time of 14 days. Adverse effects attributed to MMF, which included hemorrhagic diarrhea within the first 2 weeks of treatment, were recorded in 20% (5/25) of the dogs. CONCLUSIONS MMF can be used as an adjunctive treatment for dogs with MUE. This protocol enables reduction of prednisone treatment or, in some cases, its complete withdrawal. The possibility of intravenous administration is advantageous in cases with severe neurological abnormalities and mentation changes, often seen in MUE. Attention is warranted for gastrointestinal adverse effects, especially in the first 2 weeks of treatment.
Migraine and cognitive decline among women: prospective cohort study

Objective To evaluate the association between migraine and cognitive decline among women. Design Prospective cohort study. Setting Women’s Health Study, United States. Participants 6349 women aged 65 or older enrolled in the Women’s Health Study who provided information about migraine status at baseline and participated in cognitive testing during follow-up. Participants were classified into four groups: no history of migraine, migraine with aura, migraine without aura, and past history of migraine (reports of migraine history but no migraine in the year prior to baseline). Main outcome measures Cognitive testing was carried out at two year intervals up to three times using the telephone interview for cognitive status, immediate and delayed recall trials of the east Boston memory test, delayed recall trial of the telephone interview for cognitive status 10 word list, and a category fluency test. All tests were combined into a global cognitive score, and tests assessing verbal memory were combined to create a verbal memory score. Results Of the 6349 women, 853 (13.4%) reported any migraine; of these, 195 (22.9%) reported migraine with aura, 248 (29.1%) migraine without aura, and 410 (48.1%) a past history of migraine. Compared with women with no history of migraine, those who experienced migraine with or without aura or had a past history of migraine did not have significantly different rates of cognitive decline in any of the cognitive scores: values for the rate of change of the global cognitive score between baseline and the last observation ranged from −0.01 (SE 0.04) for past history of migraine to 0.08 (SE 0.04) for migraine with aura when compared with women without any history of migraine. Women who experienced migraine were also not at increased risk of substantial cognitive decline (worst 10% of the distribution of decline). When compared with women without a history of migraine, the relative risks for the global score ranged from 0.77 (95% confidence interval 0.46 to 1.28) for women with migraine without aura to 1.17 (0.84 to 1.63) for women with a past history of migraine. Conclusion In this prospective cohort of women, migraine status was not associated with faster rates of cognitive decline.
Impact of pay for performance on quality of chronic disease management by social class group in England

Summary Objective To examine associations between social class and achievement of selected national audit targets for coronary heart disease (CHD), diabetes and hypertension in England before and after the introduction of a major pay for performance programme in 2004. Design Secondary analysis of 2003 and 2006 national survey data for respondents with CHD and diabetes and hypertension. Setting England. Main outcome measure Achievement of national audit targets for blood pressure, blood glucose and cholesterol control. Results There were no significant differences in achievement of blood pressure targets in individuals from manual and non-manual occupational groups with diabetes (2003: 65.9% v 60.3%, 2006: 67.6% v 69.7%) or hypertension (2003: 66.2% v 66.2%, 2006: 72.8% v 71.9%) before or after the introduction of pay for performance. Achievement of the cholesterol target was also similar in individuals from manual and non-manual groups with diabetes (2003: 52.5% v 46.6%, 2006: 68.7% v 70.5%) or CHD (2003: 54.3% v 53.3%, 2006: 68.6% v 71.3%). Differences in achievement of the blood pressure target in CHD [75.8% v 84.5%; AOR 0.44 (0.21-0.90)] were evident between manual and non-manual occupational groups after the introduction of pay for performance. Conclusion The quality of chronic disease management in England was broadly equitable between socioeconomic groups before this major pay for performance programme and remained so after its introduction.
Force-position control of a robotic exoskeleton to provide upper extremity movement assistance

This paper presents an upper extremity (UE) wearable robot, ETS-MARSE and its control strategy to provide movement assistance and active rehabilitation exercises to physically disabled individuals having impaired UE function. The ETS-MARSE was designed to be worn on the lateral side of UE and is able to assist arm movements at the level of shoulder, elbow, forearm and wrist joint movements. Considering the dynamic modelling of the robot system and the UE motion which are non-linear in nature, a non-linear sliding mode control with exponential reaching law was used to manoeuvre the ETS-MARSE and to provide both passive and assisted arm movement therapy. To provide passive arm movement therapy, pre-programmed trajectories corresponding to recommended passive rehabilitation exercises were used to manoeuvre the ETS-MARSE, whereas in case of assisted rehabilitation therapy user interaction wrist force sensor signals were used to steer the ETS-MARSE in assisting the UE movements. Experiments involving healthy human subjects were performed with the developed ETS-MARSE to evaluate the controller’s performance and that of the ETS-MARSE in regards to providing the therapeutic exercises. Experimental results indicate that with the proposed control strategy, ETS-MARSE can effectively deliver rehabilitation exercises.
Q-Decomposition for Reinforcement Learning Agents

The paper explores a very simple agent design method called Q-decomposition, wherein a complex agent is built from simpler subagents. Each subagent has its own reward function and runs its own reinforcement learning process. It supplies to a central arbitrator the Q-values (according to its own reward function) for each possible action. The arbitrator selects an action maximizing the sum of Q-values from all the subagents. This approach has advantages over designs in which subagents recommend actions. It also has the property that if each subagent runs the Sarsa reinforcement learning algorithm to learn its local Q-function, then a globally optimal policy is achieved. (On the other hand, local Q-learning leads to globally suboptimal behavior.) In some cases, this form of agent decomposition allows the local Q-functions to be expressed by much-reduced state and action spaces. These results are illustrated in two domains that require effective coordination of behaviors.
Interplay of structure and mechanics in silk/carbon nanocomposites

Silk and carbon nanomaterials, such as graphene oxide, graphene, and carbon nanotubes, have complementary mechanical properties that feature superior toughness and strength, respectively. Different strategies have been devoted to developing silk/carbon nanocomposites, but challenges remain to fully integrate the mechanical advantages of these two components into one synergistic material system. In this article, we provide a critical summary of structure–mechanics relationships in silk/carbon nanocomposites and highlight the impact of the interaction between silk and carbon nanomaterials on mechanical properties of the hybrid materials. We describe the challenges involved and directions for future designs of silk/carbon nanocomposites.
Guideline for Diagnostic and Treatment of Osteonecrosis of the Femoral Head

There is a new knowledge for clinical presentations and findings of imagine in patients with osteonecrosis of the femoral head (ONFH) in recent more than ten years. According to clinical data in Chinese huge patients with ONFH, the guideline for diagnosis and treatment of ONFH has been put forward by Chinese specialists. The newer contents of guideline include the definition for predisposing risk factors of ONFH, the new knowledge for clinical manifestations, the new interpretation for changes of imagine, important differential diagnosis. Based on the supplementary and revision for widely used staging and classification system, the new Chinese staging and classification system have been established. The advantages of Chinese staging and classification system accord with clinical and pathological features, it could be predicted the prognosis, and clinical applications are convenient. The guideline gives a brief account of principles for treatment selection and treatment methods for enhancement of diagnosis and treatment for ONFH.
Relevance feedback using semantic association between indexing terms in large free text corpuses

Relevance feedback has been considered as a means of incorporating learning into information retrieval systems for quite sometime now. This paper discusses the research results of two methodologies for automatic query expansion to incorporate relevance feedback into our probabilistic information retrieval system. The first methodology employs analysis of topmost ranked documents retrieved by the user's initial query to form new keyword enriched expanded queries. These queries help the user in focusing his search to a smaller subset of the document collection. The second novel technique developed during the sourse of this research, resorts to a process similar to text mining employing 'index term association' as an underlying mechanism to expand the query with a semantic structure. We also draw a comparison of the two different methodologies using a human judge, measuring the extent of subject deviation of the expanded query from the initial/original query. The results show that significant improvement can be expected using semantic association between indexing terms in query expansion.
Microtransplantation of acetylcholine receptors from normal or denervated rat skeletal muscles to frog oocytes

Non‐technical summary Nicotinic acetylcholine receptors (nAChRs) expressed by skeletal muscle are the key proteins of the motoneuron–muscle communication necessary to induce muscle contraction. The biophysical and pharmacological characterization of the receptors in adult human skeletal muscle is limited by the difficulties associated with obtaining, and maintaining, suitable biopsy material. In this paper, we characterized some nAChR properties of innervated and denervated skeletal muscle by injecting the membranes into Xenopus oocytes. Such an approach, termed the microtransplantation technique, offers two main advantages: (1) direct characterization of the original receptors, still embedded in their natural lipid environment with their associated molecules; and (2) the possibility of using membranes isolated from postmortem frozen tissues. We demonstrate that this technique can be a very simple and useful approach to study skeletal muscle receptors and ion channels under different physiological and pathological conditions.
Semantic Feature Mining for Video Event Understanding

Content-based video understanding is extremely difficult due to the semantic gap between low-level vision signals and the various semantic concepts (object, action, and scene) in videos. Though feature extraction from videos has achieved significant progress, most of the previous methods rely only on low-level features, such as the appearance and motion features. Recently, visual-feature extraction has been improved significantly with machine-learning algorithms, especially deep learning. However, there is still not enough work focusing on extracting semantic features from videos directly. The goal of this article is to adopt unlabeled videos with the help of text descriptions to learn an embedding function, which can be used to extract more effective semantic features from videos when only a few labeled samples are available for video recognition. To achieve this goal, we propose a novel embedding convolutional neural network (ECNN). We evaluate our algorithm by comparing its performance on three challenging benchmarks with several popular state-of-the-art methods. Extensive experimental results show that the proposed ECNN consistently and significantly outperforms the existing methods.