LLukas22/scidocs huggingface dataset:
Compact and Computationally Efficient Representation of Deep Neural Networks

At the core of any inference procedure in deep neural networks are dot product operations, which are the component that require the highest computational resources. For instance, deep neural networks such as VGG-16 require up to 15 gigaoperations in order to perform the dot products present in a single forward pass, which results in significant energy consumption and therefore limit their use in resource-limited environments, e.g., on embedded devices or smartphones. A common approach to reduce the cost of inference is to reduce its memory complexity by lowering the entropy of the weight matrices of the neural network, e.g., by pruning and quantizing their elements. However, the quantized weight matrices are then usually represented either by a dense or sparse matrix storage format, whose associated dot product complexity is not bounded by the entropy of the matrix. This means that the associated inference complexity ultimately depends on the implicit statistical assumptions that these matrix representations make about the weight distribution, which can be in many cases suboptimal. In this paper we address this issue and present new efficient representations for matrices with low entropy statistics. These new matrix formats have the novel property that their memory and algorithmic complexity are implicitly bounded by the entropy of the matrix, consequently implying that they are guaranteed to become more efficient as the entropy of the matrix is being reduced. In our experiments we show that performing the dot product under these new matrix formats can indeed be more energy and time efficient under practically relevant assumptions. For instance, we are able to attain up to x42 compression ratios, x5 speed ups and x90 energy savings when we convert in a lossless manner the weight matrices of state-of-the-art networks such as AlexNet, VGG-16, ResNet152 and DenseNet into the new matrix formats and benchmark their respective dot product operation. Keywords—Neural network compression, computationally efficient deep learning, data structures, sparse matrices, lossless coding.
Phase II Trial of High-Dose , Intermittent Calcitriol ( 1 , 25 Dihydroxyvitamin D 3 ) and Dexamethasone in Androgen-Independent Prostate Cancer

Received August 1
Metabolic effects of dialyzate glucose in chronic hemodialysis: results from a prospective, randomized crossover trial.

BACKGROUND
There is no agreement concerning dialyzate glucose concentration in hemodialysis (HD) and 100 and 200 mg/dL (G100 and G200) are frequently used. G200 may result in diffusive glucose flux into the patient, with consequent hyperglycemia and hyperinsulinism, and electrolyte alterations, in particular potassium (K) and phosphorus (P). This trial compared metabolic effects of G100 versus G200.


METHODS
Chronic HD patients participated in this randomized, single masked, controlled crossover trial (www.clinicaltrials.gov: #NCT00618033) consisting of two consecutive 3-week segments with G100 and G200, respectively. Intradialytic serum glucose (SG) and insulin concentrations (SI) were measured at 0, 30, 60, 120, 180, 240 min and immediately post-HD; P and K were measured at 0, 120, 180 min and post-HD. Hypoglycemia was defined as an SG<70 mg/dL. Mean SG and SI were computed as area under the curve divided by treatment time.


RESULTS
Fourteen diabetic and 15 non-diabetic subjects were studied. SG was significantly higher with G200 as compared to G100, both in diabetic {G200: 192.8±48.1 mg/dL; G100: 154.0±27.3 mg/dL; difference 38.8 [95% confidence interval (CI): 21.2-56.4] mg/dL; P<0.001} and non-diabetic subjects [G200: 127.0±11.2 mg/dL; G100 106.5±10.8 mg/dL; difference 20.6 (95% CI: 15.3-25.9) mg/dL; P<0.001]. SI was significantly higher with G200 in non-diabetic subjects. Frequency of hypoglycemia, P and K serum levels, interdialytic weight gain and adverse intradialytic events did not differ significantly between G100 and G200.


CONCLUSION
G200 may exert unfavorable metabolic effects in chronic HD patients, in particular hyperglycemia and hyperinsulinism, the latter in non-diabetic subjects.
Analysis of a polling system for telephony traffic with application to wireless LANs

Recently, polling has been included as a resource sharing mechanism in the medium access control (MAC) protocol of several communication systems, such as the IEEE 802.11 wireless local area network, primarily to support real-time traffic. Furthermore, to allow these communication systems to support multimedia traffic, the polling scheme often coexists with other MAC schemes such as random access. Motivated by these systems, we develop a model for a polling system with vacations, where the vacations represent the time periods in which the resource sharing mechanism used is a non-polling mode. The real-time traffic served by the polling mode in our study is telephony. We use an on-off Markov modulated fluid (MMF) model to characterize telephony sources. Our analytical study and a counterpart validating simulation study show the following. Since voice codec rates are much smaller than link transmission rates, the queueing delay that arises from waiting for a poll dominates the total delay experienced by a voice packet. To keep delays low, the number of telephone calls that can be admitted must be chosen carefully according to delay tolerance, loss tolerance, codec rates, protocol overheads and the amount of bandwidth allocated to the polling mode. The effect of statistical multiplexing gain obtained by exploiting the on-off characteristics of telephony traffic is more noticeable when the impact of polling overhead is small
Delphin2: an over actuated autonomous underwater vehicle for manoeuvring research

Delphin2 is a hover capable torpedo style Autonomous Underwater Vehicle (AUV), developed at the University of Southampton to provide a test bed for research in marine robotics, primarily to enhance the manoeuvring capability of AUVs. This paper describes the mechanical design of the vehicle and its software architecture. The performance of the vehicle is presented as well as preliminary findings from the vehicle’s first fully autonomous video survey missions in Lough Erne, Northern Ireland. It is interesting to note that the low-cost of the vehicle and its development using a succession of MEng and PhD students has provided an excellent training environment for specialists in the growing area of marine autonomous vehicles.
Etiology and Treatment Modalities of Anterior Open Bite Malocclusion

1878-3317/$ e see front matter Copyright 2013, Ta http://dx.doi.org/10.1016/j.jecm.2013.01.004 The complexity of anterior open bite is attributed to a combination of skeletal, dental, soft tissue, and habitual factors. Multiple treatment strategies aimed at different etiologies of anterior open bite have been proposed. However, the tendency toward relapse after conventional or surgical orthodontic treatment has been indicated. Therefore, anterior open bite is considered one of the most challenging dentofacial deformities to treat. The aim of this article is to review the etiologies, dentofacial morphology, treatment modalities, retention, and stability of anterior open bite. The etiology of anterior open bite malocclusions is multifactorial and numerous theories have been proposed, including genetic, anatomic and environmental factors. The diagnosis and treatment modalities are variable according to the etiology. Failure of tongue posture adaptation subsequent to orthodontic and/or surgical treatment might be the primary reason for relapse of anterior open bite. Prolonged retention with fixed or removable retainers is advisable and necessary in most cases of open bite treatment. The treatment of anterior open bite remains a tough challenge to the clinician; careful diagnosis and timely intervention with proper treatment modalities and appliance selection will improve the treatment outcomes and long-term stability. Copyright 2013, Taipei Medical University. Published by Elsevier Taiwan LLC. All rights reserved.
Kinect Identity: Technology and Experience

Kinect Identity, a key component of Microsoft's Kinect for the Xbox 360, combines multiple technologies and careful user interaction design to achieve the goal of recognizing and tracking player identity.
What-and-where to match: Deep spatially multiplicative integration networks for person re-identification

Matching pedestrians across disjoint camera views, known as person re-identification (re-id), is a challenging problem that is of importance to visual recognition and surveillance. Most existing methods exploit local regions within spatial manipulation to perform matching in local correspondence. However, they essentially extract fixed representations from pre-divided regions for each image and perform matching based on the extracted representation subsequently. For models in this pipeline, local finer patterns that are crucial to distinguish positive pairs from negative ones cannot be captured, and thus making them underperformed. In this paper, we propose a novel deep multiplicative integration gating function, which answers the question of what-and-where to match for effective person re-id. To address what to match, our deep network emphasizes common local patterns by learning joint representations in a multiplicative way. The network comprises two Convolutional Neural Networks (CNNs) to extract convolutional activations, and generates relevant descriptors for pedestrian matching. This thus, leads to flexible representations for pair-wise images. To address where to match, we combat the spatial misalignment by performing spatially recurrent pooling via a four-directional recurrent neural network to impose spatial depenEmail addresses: lin.wu@uq.edu.au (Lin Wu ), wangy@cse.unsw.edu.au (Yang Wang), xueli@itee.uq.edu.au (Xue Li), junbin.gao@sydney.edu.au (Junbin Gao) Preprint submitted to Elsevier 25·7·2017 ar X iv :1 70 7. 07 07 4v 1 [ cs .C V ] 2 1 Ju l 2 01 7 dency over all positions with respect to the entire image. The proposed network is designed to be end-to-end trainable to characterize local pairwise feature interactions in a spatially aligned manner. To demonstrate the superiority of our method, extensive experiments are conducted over three benchmark data sets: VIPeR, CUHK03 and Market-1501.
Erratum to: Long-term efficacy and safety of subcutaneous pasireotide in acromegaly: results from an open-ended, multicenter, Phase II extension study

Pasireotide has a broader somatostatin receptor binding profile than other somatostatin analogues. A 16-week, Phase II trial showed that pasireotide may be an effective treatment for acromegaly. An extension to this trial assessed the long-term efficacy and safety of pasireotide. This study was an open-label, single-arm, open-ended extension study (primary efficacy and safety evaluated at month 6). Patients could enter the extension if they achieved biochemical control (GH B 2.5 lg/L and normal IGF-1) or showed clinically relevant improvements during the core study. Thirty of the 60 patients who received pasireotide (200–900 lg bid) in the core study entered the extension. At extension month 6, of the 26 evaluable patients, six were biochemically controlled, of whom five had achieved control during the core study. Normal IGF-1 was achieved by 13/26 patients and GH B 2.5 lg/L by 12/26 at month 6. Nine patients received pasireotide for C24 months in the extension; three who were biochemically controlled at month 24 had achieved control during the core study. Of 29 patients with MRI data, nine had significant (C20 %) tumor volume reduction during the core study; an additional eight had significant reduction during the extension. The most common adverse events were transient gastrointestinal disturbances; Clinical Trials Registration Number: NCT00171730. Electronic supplementary material The online version of this article (doi:10.1007/s11102-013-0478-0) contains supplementary material, which is available to authorized users. S. Petersenn (&) ENDOC Center for Endocrine Tumors, Altonaer Str. 59, 20357 Hamburg, Germany e-mail: stephan.petersenn@endoc-med.de A. J. Farrall Brain Research Imaging Centre, Western General Hospital, University of Edinburgh, Edinburgh, UK C. Block Department of Endocrinology, Diabetology and Metabolism, Antwerp University Hospital, Antwerp, Belgium S. Melmed Division of Endocrinology and Metabolism, Cedars-Sinai Medical Center, Los Angeles, CA, USA J. Schopohl Medizinische Klinik und Poliklinik IV, Campus Innenstadt, University of Munich, Munich, Germany P. Caron Service d’Endocrinologie, Maladies Métaboliques et Nutrition, Centre Hospitalier Universitaire Larrey, Toulouse, France R. Cuneo Department of Diabetes and Endocrinology, Princess Alexandra Hospital, Brisbane, Australia D. Kleinberg Neuroendocrine Unit, New York University School of Medicine, New York, NY, USA A. Colao Dipartimento di Medicina Clinica e Chirurgia, Università Federico II di Napoli, Naples, Italy M. Ruffin G. Hughes Novartis Pharma AG, Basel, Switzerland K. Hermosillo Reséndiz K. Hu Novartis Pharmaceuticals, East Hanover, NJ, USA A. Barkan Pituitary and Neuroendocrine Center, University of Michigan, Ann Arbor, MI, USA 123 Pituitary (2014) 17:132–140 DOI 10.1007/s11102-013-0478-0
Using Filter Banks in Convolutional Neural Networks for Texture Classification

Deep learning has established many new state of the art solutions in the last decade in areas such as object, scene and speech recognition. In particular Convolutional Neural Network (CNN) is a category of deep learning which obtains excellent results in object detection and recognition tasks. Its architecture is indeed well suited to object analysis by learning and classifying complex (deep) features that represent parts of an object or the object itself. However, some of its features are very similar to texture analysis methods. CNN layers can be thought of as filter banks of complexity increasing with the depth. Filter banks are powerful tools to extract texture features and have been widely used in texture analysis. In this paper we develop a simple network architecture named Texture CNN (T-CNN) which explores this observation. It is built on the idea that the overall shape information extracted by the fully connected layers of a classic CNN is of minor importance in texture analysis. Therefore, we pool an energy measure from the last convolution layer which we connect to a fully connected layer. We show that our approach can improve the performance of a network while greatly reducing the memory usage and computation. c © 2016 Elsevier Ltd. All rights reserved.
A 160-GHz Subharmonic Transmitter and Receiver Chipset in an SiGe HBT Technology

A monolithically integrated 160-GHz transmitter and receiver chipset with in-phase/quadrature baseband inputs and outputs and on-chip local oscillator (LO) generation has been implemented in a 0.25- μm silicon-germanium heterojunction bipolar transistor technology. The chipset features a three-stage differential power amplifier, a low-noise amplifier, up- and down-conversion subharmonic quadrature mixers, and an 80-GHz voltage-controlled oscillator equipped with a 1/16 frequency prescaler for frequency locking by an external phase-locked loop. To investigate the behavior of the Gilbert-cell-based subharmonic mixer operated close to fmax , the correlation between LO phases and conversion gain is studied. The conclusion suggests that the maximum conversion gain can be obtained with certain LO phases at millimeter-wave frequencies. Over the 150-168-GHz bandwidth, the transmitter delivers an output power of more than 8 dBm with a maximum 10.6-dBm output power at 156 GHz. The receiver provides a noise figure lower than 9 dB and more than 25 dB of conversion gain at 150-162 GHz, including the losses of an auxiliary input balun. The transmitter and receiver chips consume 610 and 490 mW, respectively.
A Sender-Centric Approach to Detecting Phishing Emails

Email-based online phishing is a critical security threat on the Internet. Although phishers have great flexibility in manipulating both the content and structure of phishing emails, phishers have much less flexibility in completely concealing the sender information of a phishing message. Importantly, such sender information is often inconsistent with the target institution of a phishing email. Based on this observation, in this paper we advocate and develop a sender-centric approach to detecting phishing emails by focusing on the sender information of a message instead of the content or structure of the message. Our evaluation studies based on real-world email traces show that the sender-centric approach is a feasible and effective method in detecting phishing emails. For example, using an email trace containing both phishing and legitimate messages, we show that the sender-centric approach can detect 98.7% of phishing emails while correctly classifying all legitimate messages.
Comparison of daily filgrastim and pegfilgrastim to prevent febrile neutropenia in Asian lymphoma patients.

AIM
Febrile neutropenia (FN) is a highly prevalent complication of chemotherapy, particularly in patients with non-Hodgkin's lymphoma. This study aimed to compare the efficacy of filgrastim and pegfilgrastim in Asian lymphoma patients by evaluating the incidence of FN and associated complications.


METHODS
This was a single-center, retrospective cohort study in Asian lymphoma patients who received chemotherapy with primary prophylactic granulocyte colony-stimulating factors support between January 2008 and August 2009. Data were analyzed using an intent-to-treat approach, which aimed to reflect actual prescribing practices.


RESULTS
A total of 204 Asian lymphoma patients were included in this study, with 81 patients in the filgrastim arm and 123 patients in the pegfilgrastim arm. Overall, the incidence of breakthrough FN was similar between the two groups of patients (13.6%: filgrastim arm vs 16.3%: pegfilgrastim arm; P=0.69). Neutropenic complications such as chemotherapy treatment delay and chemotherapy dose reduction were similar between the two arms.


CONCLUSION
In Asian patients, pegfilgrastim prophylaxis did not show a therapeutic advantage for preventing neutropenic outcomes compared with filgrastim prophylaxis.
Evaluation of weight based enoxaparin dosing on anti-Xa concentrations in patients with obesity

Current treatment dose of enoxaparin is based on total body weight (TBW), however dosage in obesity remains unclear. “Dose capping” commonly occurs if TBW > 100 kg minimising bleeding risk. However, this may result in under-dosing and increasing embolisation risk. The primary objective evaluated efficacy of current dosing strategies in obese patients and determined if resultant anti-Xa concentrations (aXaC) were therapeutic. The secondary objective was to investigate if an uncapped 0.75–0.85 mg/kg (TBW) twice daily dose, advocated by previous authors, results in therapeutic aXaC (0.5–1.0 IU/ml). This retrospective study included 133 patients with a median TBW of 128 kg, producing 59% therapeutic, 15% sub-therapeutic and 26% supra-therapeutic aXaC. Approximately 60% of patients in each dose group (< 0.75, 0.75–0.85 and > 0.85 mg/kg) had a therapeutic aXaC, however the percentage of sub-therapeutic versus supra-therapeutic was higher in the < 0.75 (27% vs 9%) and > 0.85 mg/kg (10% vs 34%) groups respectively. Most patients who weighed 100–119 kg (TBW) received doses > 0.85 mg/kg, however 32% had toxic aXaC. Those between 120 and 139 kg (TBW) had a high percentage of therapeutic aXaC (87%) when dosed < 0.75 mg/kg and a high percentage of supra-therapeutic aXaC (71%) when dosed > 0.85 mg/kg; although numbers were low. Dose reduction occurred in patients > 140 kg (TBW), however < 0.75 mg/kg resulted in higher percentage of sub-therapeutic aXaC (42%). Dosing at 0.75–0.85 mg/kg results in 62% of therapeutic, 14% sub-therapeutic and 24% supra-therapeutic aXaC. This appears to be a “safe” starting dose-range, however all obese patients should have aXaC monitoring due to high inter-patient variability.
Paternal long-term exercise programs offspring for low energy expenditure and increased risk for obesity in mice.

Obesity has more than doubled in children and tripled in adolescents in the past 30 yr. The association between metabolic disorders in offspring of obese mothers with diabetes has long been known; however, a growing body of research indicates that fathers play a significant role through presently unknown mechanisms. Recent observations have shown that changes in paternal diet may result in transgenerational inheritance of the insulin-resistant phenotype. Although diet-induced epigenetic reprogramming via paternal lineage has recently received much attention in the literature, the effect of paternal physical activity on offspring metabolism has not been adequately addressed. In the current study, we investigated the effects of long-term voluntary wheel-running in C57BL/6J male mice on their offspring's predisposition to insulin resistance. Our observations revealed that fathers subjected to wheel-running for 12 wk produced offspring that were more susceptible to the adverse effects of a high-fat diet, manifested in increased body weight and adiposity, impaired glucose tolerance, and elevated insulin levels. Long-term paternal exercise also altered expression of several metabolic genes, including Ogt, Oga, Pdk4, H19, Glut4, and Ptpn1, in offspring skeletal muscle. Finally, prolonged exercise affected gene methylation patterns and micro-RNA content in the sperm of fathers, providing a potential mechanism for the transgenerational inheritance. These findings suggest that paternal exercise produces offspring with a thrifty phenotype, potentially via miRNA-induced modification of sperm.
Studies on Economic Feasibility of an Autonomous Power Delivery System Utilizing Alternative Hybrid Distributed Energy Resources

An economic evaluation of a network of distributed energy resources (DERs) forming an autonomous power delivery system in an Indian scenario has been made. The mathematical analysis is based on the application of a real valued cultural algorithm (RVCA). The RVCA-evaluated total annual costs for the autonomous microgrid system utilizing both solar module and fuel cells as DERs and solar module and bio-mass gassifier unit as DERs have been compared. Different types of consumers together form a microgrid with the optimal supply of power from DERs. The optimal power generation conditions have been obtained pertaining to minimum cost of microgrid system. The results for different loading scenarios, using hybrid solar-biomass gassifier unit are found to be more cost competitive. A reduction of 8.1% in the annual cost is obtained using solar module-biomass gassifier unit to that using solar module-fuel cell for the same load demand in microgrid operation.