Miracle-dz/UniFAR-FTUs huggingface dataset:
Correlations Between the SF-36, the Oswestry-Disability Index and Rolland-Morris Disability Questionnaire in Patients Undergoing Lumbar Decompression According to Types of Spine Origin Pain

Study Design: Cross-sectional study. Objective: To determine the correlation between SF-36 (a measure for overall health status in patients) and Oswestry-Disability Index (ODI) or Rolland-Morris Disability Questionnaire (RMDQ) confined to spine according to the type of pain from the spine. Summary of Background Data: Data showed moderate correlation between ODI and SF-36 Physical Component Score (PCS), Physical Functioning (PF) (r=−0.46), Physical Role Functioning (RP) (r=−0.284), Bodily Pain (BP) (r=−0.327), and Mental Component Score (MCS), Emotional Role Functioning (r=−0.250), Social Role Functioning (r=0.254), Vitality (r=0.296). Materials and Methods: Between January 1, 2008 and December 31, 2013, a total of 69 patients were enrolled in this study. They were diagnosed with lumbar spinal stenosis and underwent decompression surgery such as laminotomy in this hospital. The 3 standardized questionnaires (ODI, RMDQ, and SF-36) were given to these patients, at least 1 year after the surgery. Results: ODI and SF-36 had a statistically significant (P=0.001) and moderate correlation. Small correlations were also seen between Physical Functioning (r=−0.46), Physical Role Functioning (r=−0.284), and Bodily Pain (r=−0.327) of SF-36 PCS and ODI, and between Emotional Role Functioning (r=−0.250), Social Role Functioning (r=−0.254), and Vitality (r=−0.296) of SF-36 Mental Component Score and ODI. Items in ODI for the level of pain while standing and traveling were mostly related to axial back pain, while item of lifting was related to referred buttock pain. Sleeping disturbance section in the ODI was mainly caused by radiated leg pain. In addition, RMDQ was also associated to the 3 types of pain. Conclusions: Moderate correlation was found between ODI or RMDQ as a condition-specific outcome and the SF-36, indicating overall health status. ODI was found to be a more adequate measure to evaluate axial back pain rather than referred pain or radiating pain. RMDQ was adequate to measure the health status and to evaluate the 3 types of spine pain. These 3 instruments could therefore provide the clinician with complementary information about the patient’s status.
Guidelines for the Management of Stroke

Stroke is one of the leading causes of death worldwide and should be considered as a medical emergency. It is caused by obstruction of blood flow to the brain and neurons. It is of two types namely ischemic and hemorrhagic. The major risk factors of stroke are hypertension, cardiac diseases, diabetes mellitus, hyperlipidemia, cigarette smoking and alcohol consumption. ABCD2 score is used to predict the risk of incidence of stroke after a transient ischemic attack. Computed tomography and magnetic resonance imaging are generally used to detect areas of ischemia and bleeding in brain. Tissue plasminogen activator and aspirin are the preferred first line treatment options for treating ischemic stroke while hemorrhagic stroke has no standard therapy. Regular physician visits and clinical check-ups reduce the chance of occurrence of secondary stroke.
SIMPO

While CPU architectures are incorporating many more cores to meet ever-bigger workloads, advance in fault-tolerance support is indispensable for sustaining system performance under reliability constraints. Emerging non-volatile memory technologies are yielding fast, dense, and energy-efficient NVRAM that can dethrone SSD drives for persisting data. Research on using NVRAM to enable fast in-memory data persistence is ongoing. In this work, we design and implement a persistent object framework, dubbed scalable in-memory persistent object (SIMPO), which exploits NVRAM, alongside DRAM, to support efficient object persistence in highly threaded big data applications. Based on operation logging, we propose a new programming model that classifies functions into instant and deferrable groups. SIMPO features a streamlined execution model, which allows lazy evaluation of deferrable functions and is well suited to big data computing workloads that would see improved data locality and concurrency. Our log recording and checkpointing scheme is effectively optimized towards NVRAM, mitigating its long write latency through write-combining and consolidated flushing techniques. Efficient persistent object management with features including safe references and memory leak prevention is also implemented and tailored to NVRAM. We evaluate a wide range of SIMPO-enabled applications with machine learning, high-performance computing, and database workloads on an emulated hybrid memory architecture and a real hybrid memory machine with NVDIMM. Compared with native applications without persistence, experimental results show that SIMPO incurs less than 5% runtime overhead on both platforms and even gains up to 2.5× speedup and 84% increase in throughput in highly threaded situations on the two platforms, respectively, thanks to the streamlined execution model.
How app update affects app download in iOS appstore

Mobile stores (appstores) are emerging digital distribution platforms with explosive growth, in which the mobile applications (apps) are directly published by the app developers and downloaded by the end users. Appstores attract a lot attention of academia, there are increasingly studies on many aspects of appstores, especially update or release strategy of apps. In this paper, we measured a third-party appstore and introduced a metric, named “Pulling Rate” to quantify the effect of update events on downloads through case study. The results showed that in the first ten days after update, downloads will increase about three times about average downloads. However, after about 45 days after update event, the effect of update event on downloads will exists no more. These results are useful for app developers to help with determining their release strategies.
Refractive lenticule extraction small incision lenticule extraction: A new refractive surgery paradigm

Small incision lenticule extraction (SMILE), a variant of refractive lenticule extraction technology is becoming increasingly popular, as a flapless and minimally invasive form of laser vision correction (LVC) for the treatment of myopia and myopic astigmatism. This review aims at summarizing the principles, surgical technique, and clinical outcomes in terms of visual and refractive results, safety, efficacy, postoperative dry eye, aberrations, and biomechanics of SMILE and its comparison with other conventional techniques of LVC, such as laser in situ keratomileusis (LASIK) and photorefractive keratectomy (PRK). Recent advancements in the laser frequency and energy delivery patterns, instrumentation, and surgical techniques have shown significant improvement in the visual recovery and outcomes after SMILE, compared to the initial results published by Sekundo and Shah et al. Most of the recently published literature on long-term outcomes of SMILE shows excellent stability of the procedure, especially for higher myopia. In terms of the postoperative dry eye, SMILE shows a clear advantage over LASIK as numerous studies have shown significant differences about the Schirmer's, Tear film break up time, corneal sensitivity, and corneal nerve regeneration to be better following SMILE compared to LASIK. There is some evidence that since the Bowman's membrane (BM) and the anterior lamellae remain intact after SMILE, this may be a potential advantage for corneal biomechanics over LASIK and PRK where the BM is either severed or ablated, respectively, however, the data on biomechanics are inconclusive at present. Overall, this procedure has proved to be promising, delivering equivalent, or better visual and refractive results to LASIK and providing clear advantage in terms of being a flapless, minimally invasive procedure with minimal pain and postoperative discomfort thus offering high patient satisfaction.
Spatially Coherent Feature Learning for Pose-Invariant Facial Expression Recognition

Feature learning has enjoyed much attention and achieved good performance in recent studies of image processing. Unlike the required training conditions often assumed there, far less labeled data is available for training emotion classification systems. In addition, current feature learning is typically performed on an entire face image without considering the dependency between features. These approaches ignore the fact that faces are structured and the neighboring features are dependent. Thus, the learned features lack the power to describe visually coherent facial images. Our method is therefore designed with the goal of simplifying the problem domain by removing expression-irrelevant factors from the input images, with a key region-based mechanism, which is an effort to reduce the amount of data required to effectively train the feature-learning methods. Meanwhile, we can construct geometric constraints between the key regions and its detected positions. To this end, we introduce a Spatially Coherent featurelearning method for Pose-invariant Facial Expression Recognition (SC-PFER). In our model, we first perform face frontalization through a 3D pose-normalization technique, which could normalize poses while preserving the identity information through synthesizing frontal faces for facial images with arbitrary views. Subsequently, we select a sequence of key regions around 51 key points in the synthetic frontal face images for efficient unsupervised feature learning. Finally, we introduce a linkage structure over the learning-based features and the corresponding geometry information of each key region to encode the dependencies of the regions. Our method, on the whole, does not require training multiple models for each specific pose and avoids separating training and parameter tuning for each pose. The proposed framework has been evaluated on two benchmark databases, BU-3DFE and SFEW, for pose-invariant Facial Expression Recognition (FER). The experimental results demonstrate that our algorithm outperforms current state-of-the-art FER methods. Specifically, our model achieves an improvement of 1.72% and 1.11% FER accuracy, on average, on BU-3DFE and SFEW, respectively.
Binary Set Embedding for Cross-Modal Retrieval

Cross-modal retrieval is such a challenging topic that traditional global representations would fail to bridge the semantic gap between images and texts to a satisfactory level. Using local features from images and words from documents directly can be more robust for the scenario with large intraclass variations and small interclass discrepancies. In this paper, we propose a novel unsupervised binary coding algorithm called binary set embedding (BSE) to obtain meaningful hash codes for local features from the image domain and words from text domain. Understanding image features with the word vectors learned from the human language instead of the provided documents from data sets, BSE can map samples into a common Hamming space effectively and efficiently where each sample is represented by the sets of local feature descriptors from image and text domains. In particular, BSE explores relationship among local features in both feature level and image (text) level, which can balance the sensitivity of each other. Furthermore, a recursive orthogonalization procedure is applied to reduce the redundancy of codes. Extensive experiments demonstrate the superior performance of BSE compared with state-of-the-art cross-modal hashing methods using either image or text queries.
Prediction of self-compacting concrete strength using artificial neural networks

Despite the widespread use of self-compacting concrete (SCC) in construction in the last decades, there is not yet a robust quantitative method, available in the literature, which can reliably predict their strength based on the mix components. This is mainly due to the highly non-linear behaviour exhibited by the compressive strength in relation to the components of the concrete mixtures. In the present paper, the application of artificial neural networks (ANNs) to predict the mechanical characteristics of SCC has been investigated. Specifically, ANN models for the prediction of the 28-days compressive strength of admixture-based self-compacting concrete (based on experimental data available in the literature) are presented. The comparison of the derived results with experimental findings demonstrates the promising potential of using back propagation neural networks for the reliable and robust approximation of the compressive strength of self-compacting concrete.
Australian Rainforest Fruits: A Field Guide

This beautifully illustrated field guide covers 504 of the most common fruiting plants found in Australia's eastern rainforests, as well as a few species that are rare in the wild but generally well-known. These spectacular plants can be seen from Cape York to Victoria, with some species also found in the Northern Territory, Western Australia and overseas. Rainforest fruits are often beautifully coloured, and in this guide the species are arranged by colour of ripe fruit, then by size and form. Five broad categories – pink to purple, blue to black, yellow and orange to red, green to brown, and white – allow people with even limited botanical knowledge to identify rainforest fruits. Each species description is accompanied by a leaf drawing, a distribution map, and diagnostic characters to help the reader distinguish similar species. Australian Rainforest Fruits includes stunning artwork by Australia’s leading natural history artist, William T Cooper. It will be sought not just by bushwalkers and natural history enthusiasts, but also by those who admire botanical art at its best.
Determination of Herd Prevalence of Brucellosis using Rose Bengal Plate Test and Indirect ELISA

The present study was aimed at diagnosis of brucellosis in cattle and buffalo using RBPT and iELISA and comparing the two tests. The animals belonged to a cattle shelter house (Gaushala). Out of 303 sera samples collected, 125 (41.25%) were positive by RBPT and among 125 positive samples, 2 were of male and other 123 were of female animals. On the other hand the results of ELISA were tripartite and 142 (46.86%), 22 (07.26%) and 139 (45.54%) samples were found as positive, moderately positive and negative, respectively. Overall by combining the both type of positive results, 164 (54.12%) samples were found positive by iELISA. On herd level, this was much higher than reports from most of earlier workers. On taking iELISA as reference test, the sensitivity and specificity of RBPT were calculated as 80.78% and 100%, respectively and the level of agreement between two tests was 0.871. But three categories of variations were observed between two tests, i.e. eighteen samples were positive in RBPT but negative in ELISA, 49 were negative in RBPT but positive in ELISA and 12 were negative in RBPT but moderately positive in ELISA.
Influence of Aloe barbadensis (Miller 1768) Extract on White Blood Cells Counts as Immunological Parameters of Adult Heterobranchus Bidorsalis (Geoffroy Saint-Hilaire 1809)

Aloe barbadensis extract was incorporated in the feeds of adult Heterobranchus bidorsalis at concentrations of 0.0, 25.0, 50.0, 75.0, 100.0, and 125.0 mg/Kg of feeds in triplicates. Fresh gel was mixed with feeds and sundried. The fish were fed at 6% body weight divided into two rations per day. The fish were fed for 14 days before being analysed for hematological parameters such as total white blood cell count, lymphocyte, neutrophils counts, eosinophils counts, basophils counts as well as monocyte counts. The monocytes and eosinophils were significantly lower (p<0.05) in the treated fish while basophils were not encountered at all. The neutrophils and lymphocytes being the immune responsive leucocytes were increased in circulation due to Aloe barbadensis exposure. Aloe barbadensis extract is therefore recommended as fish supplements at concentration of 50.0 to 75.0 mg/Kg of feeds for adult Heterobranchus
On a class of non-coaxial plasticity models for granular soils

The non-coaxiality of the directions of principal stresses and principal plastic strain rates in granular soils under stress rotations has long been observed and recognized in soil tests using both simple shear and hollow cylinder apparatuses. A few constitutive theories have also been proposed in the literature to account for the effect of stress rotations and the subsequent non-coaxial soil behaviour, particularly in the context of shear band analysis. However, the lack of corresponding general numerical methods makes it difficult to investigate the influence of non-coaxial stress–strain behaviour on the results of geotechnical boundary value problems. This paper presents a numerical evaluation of a class of non-coaxial, elastic–plastic models that are developed by combining the conventional plastic potential theory and the double shearing theory. The general non-coaxial constitutive theories are first formulated and then a finite element implementation of the theories is carried out. To evaluate the non-coaxial theories, the problem of simple shear of soils is chosen to investigate the predicted behaviour of soils under simple shear loading conditions where the axes of principal stresses rotate. In particular, the influence of initial stress states and the degree of non-coaxiality are examined. It is found that the numerical results predicted using the non-coaxial model are in general agreement with the experimental observations reported in the literature.
GPU Performance vs. Thread-Level Parallelism

Graphics Processing Units (GPUs) leverage massive thread-level parallelism (TLP) to achieve high computation throughput and hide long memory latency. However, recent studies have shown that the GPU performance does not scale with the GPU occupancy or the degrees of TLP that a GPU supports, especially for memory-intensive workloads. The current understanding points to L1 D-cache contention or off-chip memory bandwidth. In this article, we perform a novel scalability analysis from the perspective of throughput utilization of various GPU components, including off-chip DRAM, multiple levels of caches, and the interconnect between L1 D-caches and L2 partitions. We show that the interconnect bandwidth is a critical bound for GPU performance scalability. For the applications that do not have saturated throughput utilization on a particular resource, their performance scales well with increased TLP. To improve TLP for such applications efficiently, we propose a fast context switching approach. When a warp/thread block (TB) is stalled by a long latency operation, the context of the warp/TB is spilled to spare on-chip resource so that a new warp/TB can be launched. The switched-out warp/TB is switched back when another warp/TB is completed or switched out. With this fine-grain fast context switching, higher TLP can be supported without increasing the sizes of critical resources like the register file. Our experiment shows that the performance can be improved by up to 47% and a geometric mean of 22% for a set of applications with unsaturated throughput utilization. Compared to the state-of-the-art TLP improvement scheme, our proposed scheme achieves 12% higher performance on average and 16% for unsaturated benchmarks.
Mixed Valence Perovskite Cs2Au2I6: A Potential Material for Thin‐Film Pb‐Free Photovoltaic Cells with Ultrahigh Efficiency

New light is shed on the previously known perovskite material, Cs2Au2I6, as a potential active material for high‐efficiency thin‐film Pb‐free photovoltaic cells. First‐principles calculations demonstrate that Cs2Au2I6 has an optimal band gap that is close to the Shockley–Queisser value. The band gap size is governed by intermediate band formation. Charge disproportionation on Au makes Cs2Au2I6 a double‐perovskite material, although it is stoichiometrically a single perovskite. In contrast to most previously discussed double perovskites, Cs2Au2I6 has a direct‐band‐gap feature, and optical simulation predicts that a very thin layer of active material is sufficient to achieve a high photoconversion efficiency using a polycrystalline film layer. The already confirmed synthesizability of this material, coupled with the state‐of‐the‐art multiscale simulations connecting from the material to the device, strongly suggests that Cs2Au2I6 will serve as the active material in highly efficient, nontoxic, and thin‐film perovskite solar cells in the very near future.
Endocrine disrupting chemicals, 4‐nonylphenol, bisphenol A and butyl benzyl phthalate, impair metabolism of estradiol in male and female rats as assessed by levels of 15α‐hydroxyestrogens and catechol estrogens in urine

Bisphenol A (BPA), 4‐nonylphenol (NP) and butyl benzyl phthalate (BBP), termed endocrine‐disrupting chemicals, are known to mimic estrogen activity. The effects of these chemicals on 17β‐estradiol (E2) metabolism in vivo in rats were examined. Male and female rats were given NP (250 mg kg–1 day–1), BPA (250 μg kg–1 day–1) or BBP (500 mg kg–1 day–1) by gavage for 14 days, followed by a single intraperitoneal injection of E2 (5 mg kg–1) on the final day. The urinary excretion over 72 hours of 2‐hydroxyestrone 1‐N‐acetylcysteine thioether, 2‐hydroxyestrone 4‐N‐acetylcysteine thioether, 4‐hydroxyestrone 2‐N‐acetylcysteine thioether, 2‐hydroxy‐17β‐estradiol (2‐OHE2), 2‐hydroxyestrone (2‐OHE1), 4‐hydroxy‐17β‐estradiol, 4‐hydroxyestrone, 15α‐hydroxyestriol (E4), 15α‐hydroxy‐17β‐estradiol and 15α‐hydroxyestrone was measured. Increases in urinary excretion of 2‐OHE1 and decreases in E4 were observed in males treated with NP or BBP. Decreases in urinary excretion of 2‐OHE2 and E4 were observed in males treated with BPA. Decreases in urinary excretion of 2‐OHE1 and 2‐OHE2 were observed in females treated with BBP. Normalized liver and weights were increased in both sexes treated with NP or BBP. Histologic observations revealed marked changes in the distal tubules and collecting ducts in the kidneys of rats exposed to NP and BBP, and hypertrophy in the hepatocytes of the centrilobular zone of the liver. No BPA‐related effects on organ weight and on liver or kidney histopathology were found. These results suggest that the 14 day oral dosing of NP and BBP disrupted E2 metabolism, resulting from marked morphological and functional alterations in the liver and kidneys. In addition, BPA could induce metabolic and endocrine disruption.