LLukas22/scidocs huggingface dataset:
Modeling Password Guessing with Neural Networks

Passwords still dominate the authentication space, but they are vulnerable to many different attacks; in recent years, guessing attacks in particular have notably caused a few high-profile information leaks. Password strength checkers, which attempt to guard against guessing attacks by enforcing heuristics like length and character variety, only model resistance to these brute-force attacks by proxy. In this paper, we reproduce the work of Melicher et. al [1], designing a strength checker that directly bases its ratings on resistance to guessing attacks. We provide a qualitative comparison of the ratings output by this system to those of a popular heuristic one, zxcvbn.
Block Tensor Unfoldings

Within the field of numerical multilinear algebra, block tensors are increasingly important. Accordingly, it is appropriate to develop an infrastructure that supports reasoning about block tensor computation. In this paper we establish concise notation that is suitable for the analysis and development of block tensor algorithms, prove several useful block tensor identities, and make precise the notion of a block tensor unfolding.
Experience of CyberKnife Robotic Radiosurgery in treating intra and extra-cranial tumours: A review of outcomes.

OBJECTIVE
To determine the success rate and complication of CyberKnife Robotic Radiosurgery for treating intracranial and extra cranial tumours.


METHODS
The cross-sectional observational study was carried out at the Department of CyberKnife Robotic Radiosurgery at the Jinnah Postgraduate Medical Centre, Karachi, and reviewed data related to a year from December 2012 to December 2013. Patients referred from different hospitals within and outside Pakistan for stereotactic radiosurgery were included. The patients had benign tumours less than 7cm size, post-operative residual tumour and recurrent tumour with post-radiotherapy. Patients were followed up every three months with contrast magnetic resonance imaging. Radiosurgery was considered successful if patients improved clinically with radiologically stable disease or if there was interval reduction in the size of tumour. SPSS 17 was used for data analysis.


RESULTS
Initially, 260 patients were selected, but 9(3.5%) were lost, and the final sample size was 251(96.5%). Clinically successful outcome results were seen in 225(90%) patients, while 8(3%) showed no change in symptoms and 18(7%) patients' follow-up is awaited. Radiological improvement was noted in 218(87%); stable disease in 138(55%) and 80(32%) cases showed more than 30% reduction in size after 6-12 months of follow-up. Only 5(2%) cases showed subtle increase in size within 3-month interval due to post-radiation oedema. Acute transient post-radiation changes were seen in 25(10%) patients, sub-acute changes in 4(1.59%) and 1(0.3%) patient showed radionecrosis after 9-month interval.


CONCLUSIONS
Cyberknife was an effective, safe and successful treatment alternative to surgery in benign and malignant tumours with low risk of post-radiotherapy complication compared to conventional radiation.
Conflict Resolution and Preference Learning in Ubiquitous Environment

Building intelligent environment is one of crucial challenges for ubiquitous computing developers. To make the environment adapt rationally according to the desire of users, the system should be able to guess users’ interest, by learning users’ behavior, habit or preference. While learning the user preference, dealing with uncertainty and conflict resolution is of the utmost importance. When many users are involved in a ubiquitous environment, the decisions of one user can be affected by the desires of others. This makes learning and prediction of user preference difficult. To address the issue, we propose an approach of user preference learning which can be used widely in context-aware systems. We use Bayesian RN-Metanetwork, a multilevel Bayesian network to model user preference and priority. Keyword: Conflict resolution, preference learning, Bayesian network, Bayesian RN-Metanetwork, context awareness.
A Minimum Delay Routing Algorithm Using Distributed Computation

73 generalized vertex median of a weighted graph, " Operations Res., pp. 955-961, July 1967. and 1973, respectively. He spent two and a half years at Bell Laboratories , Murray Hill, NJ, developing telemetrized automatic surveillance and control systems. He is now Manager at Data Communications Systems, Vienna, VA, where he has major responsibilities in research and development of network analysis and design capabilities, and has applied these capabilities in the direction of projects ranging from feasability analysis and design of front end processors for the Navy to development of network architectures for the FAA. NY, responsible for contributing to the ongoing research in the areas of large network design, topological optimization for terminal access, the concentrator location problem, and flow and congestion control strategies for packet switching networks. At present, Absfruct-An algorithm is defined for establishing routing tables in the individual nodes of a data network. The routing fable at a node i specifies, for each other node j , what fraction of the traffic destined far node j should leave node i on each of the links emanating from node i. The algorithm is applied independently at each node and successively updates the routing table at that node based on information communicated between adjacent nodes about the marginal delay to each destination. For stationary input traffic statistics, the average delay per message through the network converges, with successive updates of the routing tables, to the minimum average delay over all routing assignments. The algorithm has the additional property that the traffic to each destination is guaranteed to be loop free at each iteration of the algorithm. In addition, a new global convergence theorem for non-continuous iteration algorithms is developed. INTRODUCTION T HE problem of routing assignments has been one of the most intensively studied areas in the field of data networks in recent years. These routing problems can be roughly classified as static routing, quasi-static routing, and dynamic routing. Static routing can be typified by the following type of problem. One wishes to establish a new data network and makes various assumptions about the node locations, the link locations, and the capacities of the links. Given the traffic between each source and destination, one can calculate the traffic on each link as a function of the routing of the traffic. If one approximates the queueing delays on each link as a function of the link traffic, one can …
Differential effects of fatness, fitness and physical activity energy expenditure on whole-body, liver and fat insulin sensitivity

The relative contributions of fitness (maximal oxygen uptake), physical activity energy expenditure (PAEE) and fatness to whole-body, liver and fat insulin sensitivity is uncertain. The aim of this study was to determine whether fitness and PAEE are associated with whole-body, liver and fat insulin sensitivity independently of body fat. We recruited 25 men (mean [SD] age 53 [6] years). Whole-body (M value) and liver (percentage suppression of endogenous glucose output) insulin sensitivity were estimated using a hyperinsulinaemic–euglycaemic clamp. Insulin sensitivity in fat (insulin sensitivity index for NEFA) was estimated during an OGTT. Total and truncal fat were measured by dual-energy X-ray absorptiometry, fitness by treadmill, and PAEE (n = 21) by 3 day heart rate monitoring and Baecke questionnaire. In univariate analyses, fatness was strongly associated with insulin sensitivity (whole-body, liver and fat). Fitness was associated with whole-body (r = 0.53, p < 0.007) and liver (0.42, p = 0.04) insulin sensitivity, while PAEE was associated with liver insulin sensitivity (r = 0.55, p = 0.01). Regression models were established to describe associations between fatness, fitness and physical activity and measures of insulin sensitivity (whole-body, fat and liver) as outcomes. Only fatness was independently associated with whole-body insulin sensitivity (B coefficient −0.01, p = 0.001). Fitness was not associated with any outcome. Only PAEE was independently associated with liver insulin sensitivity (B coefficient 13.5, p = 0.02). Fatness explains most of the variance in whole-body insulin sensitivity. In contrast, PAEE explains most of the variance in liver insulin sensitivity.
Determination of selenium in selected food samples from Argentina and estimation of their contribution to the Se dietary intake.

An optimised FI-HGAAS method was applied to determine the total selenium concentrations in selected high consumption food (fish, beef, chicken, milk, rice, wheat flour, egg) and to estimate their contribution to the Argentinean dietary intake, whose information is scarce nowadays. Through several optimisation steps a suitable method was achieved showing satisfactory figures of merit for all matrices. Average recovery was 96%, RSD<5%, LODs ranged 2.0-7.0 μg kg(-1) and the accuracy was assessed using DOLT-3 NRC certified reference material. Meat and eggs showed the highest values (in μg kg(-1), beef: 42-153; chicken: 62-205; fish: 94-314; canned tuna: 272-282; eggs: 134-217), minor values were found for wheat flour (22-42), rice: (<22), pasta (47-64) and milk (<7-9). An estimated intake of 32 and 24 μg day(-1) for adult men and women, respectively, suggested a deficient Se intake, leading to further comprehensive surveys of Se occurrence in Argentina.
Fixed point implementation of Kalman filtering for AC drives : a case study using TMS 320 F 24 x DSP

The real-time digital implementation of the Kalman filter requires a very fast signal processor specialised and optimised to perform complex mathematical calculations and manipulate a large amount of data. In fact, the algorithm is computationally intensive, and all of the steps involved require vector and/or matrix operation. In this paper the analysis of an actual fixed point implementation of the Kalman filter is discussed based on a last generation μC DSP (TMS320F240). The considered case study refers to rotor speed and position estimation in AC drives when using low resolution position transducers. It is shown that the adopted processor is suitable for an efficient and relatively simple implementation of the filter allowing to increase the resolution in speed calculation with respect to the classical differentiation solution. Introduction As known, the Kalman filter is an optimal recursive algorithm which provides the minimum variance state estimation for a time-varying linear system. It is able to tolerate system modelling and measurement errors, which are considered as noise processes in the state estimation. It processes all available measurements regardless of their precision, to provide a quick and accurate estimate of the variables of interest, also achieving a fast convergence. Its extension to non-linear systems, the Extended Kalman Filter (EKF), does not assure the minimum variance estimate and no convergence proof can be given. Nevertheless, the approach behaves well in most situations, as demonstrated by numerous applications (e.g. [1][2]). For a straightforward application of this algorithm, the non-linear discrete-time state equations of the system are written in the following form: ( ) ( ) k k k k k k k k , , , , v u x h y w u x f x + = + = + k k 1 R vv í Q ww w T T = = = = ) E( ) cov( ) E( ) cov( (1) where xk is the system state vector, yk is the system output, uk is the system input, wk and vk are zeromean white Gaussian additive noises with covariance Q and R, respectively (independent from the system state xk). The vector wk takes into account the system disturbances and model inaccuracies, while v represents the measurement noise. A block diagram of the EKF for the system (1) is given in Fig. 1 together with the list of the steps of a recursive implementation [3]. The filter provides a first estimate of x ( x ~ , prediction) based on the model equations supposing that the model noise is zero. Then the measurements and noise models are used to generate the sub-optimal estimate x̂ . P ~ and P̂ are, respectively, the prediction and the estimation error covariance matrices. In the following sections a brief review of the basic applications of the EKF to the estimation of the state variables of electrical drives is reported. I) ) , ~ ( ~ ) , ˆ ( ~ u x h y u x f = x = x x x x f F ˆ ) ( = ∂ ∂ = x x x x h H ˆ ) ( = ∂ ∂ = II) Q F P F P + = T ˆ ~ III) [ ] 1 T T ~ ~ − + = R H P H H P K IV) ) ~ ( ~ ˆ y y K x = x − + V) P KH P P ~ ~ ˆ − = y x̂ u
Stan : A probabilistic programming language for Bayesian inference and optimization

Abstract Stan is a free and open-source C++ program that performs Bayesian inference or optimization for arbitrary user-specified models and can be called from the command line, R, Python, Matlab, or Julia, and has great promise for fitting large and complex statistical models in many areas of application. We discuss Stan from users’ and developers’ perspective and illustrate with a simple but nontrivial nonlinear regression example.
Evaluation of maxillary incisive canal characteristics related to dental implant treatment with computerized tomography: a clinical multicenter study.

BACKGROUND
A close anatomic relationship between the incisive canal and the roots of the central maxillary incisors should be kept in mind during dental-implant treatment in the anterior maxilla. The aim of the present study is to analyze incisive canal characteristics on computed tomography (CT) sections and to evaluate its relation to bone anterior to the canal with regard to dental implantation.


METHODS
A total of 933 partially edentulous and/or edentulous patients scheduled for implant insertion in four dental clinics enrolled in the present study. The following were measured and recorded from CT sections for analysis: 1) diameter and length of the incisive canal; 2) width and length of the bone anterior to the canal; 3) palatal bone width and length; and 4) root width and length of the central incisor.


RESULTS
Mean canal length was 10.86 ± 2.67 mm, and mean diameter was 2.59 ± 0.91 mm. Canal length was shortened in edentulous anterior maxilla compared to dentate maxilla. However, canal diameter did not show any difference between dentate and edentulous groups. Males had a longer and wider incisive canal than females. Canal shape was mostly cylindrical in 40.73% of images. No correlation was found with mean canal length and mean canal diameter according to age.


CONCLUSIONS
Although variations exist in every patient, the findings from this study suggest that sex and dental status are important factors that can affect incisive canal characteristics and amount of bone anterior to the canal. Clinicians should perform careful planning using CT scans before performing dental implant surgeries in premaxillary region.
Natural genetic variation in plant photosynthesis.

Natural genetic variation in plant photosynthesis is a largely unexplored and as a result an underused genetic resource for crop improvement. Numerous studies show genetic variation in photosynthetic traits in both crop and wild species, and there is an increasingly detailed knowledge base concerning the interaction of photosynthetic phenotypes with their environment. The genetic factors that cause this variation remain largely unknown. Investigations into natural genetic variation in photosynthesis will provide insights into the genetic regulation of this complex trait. Such insights can be used to understand evolutionary processes that affect primary production, allow greater understanding of the genetic regulation of photosynthesis and ultimately increase the productivity of our crops.
Nurse staffing, burnout, and health care-associated infection.

BACKGROUND
Each year, nearly 7 million hospitalized patients acquire infections while being treated for other conditions. Nurse staffing has been implicated in the spread of infection within hospitals, yet little evidence is available to explain this association.


METHODS
We linked nurse survey data to the Pennsylvania Health Care Cost Containment Council report on hospital infections and the American Hospital Association Annual Survey. We examined urinary tract and surgical site infection, the most prevalent infections reported and those likely to be acquired on any unit within a hospital. Linear regression was used to estimate the effect of nurse and hospital characteristics on health care-associated infections.


RESULTS
There was a significant association between patient-to-nurse ratio and urinary tract infection (0.86; P = .02) and surgical site infection (0.93; P = .04). In a multivariate model controlling for patient severity and nurse and hospital characteristics, only nurse burnout remained significantly associated with urinary tract infection (0.82; P = .03) and surgical site infection (1.56; P < .01) infection. Hospitals in which burnout was reduced by 30% had a total of 6,239 fewer infections, for an annual cost saving of up to $68 million.


CONCLUSIONS
We provide a plausible explanation for the association between nurse staffing and health care-associated infections. Reducing burnout in registered nurses is a promising strategy to help control infections in acute care facilities.
Functional magnetic resonance imaging of the effects of low-frequency transcutaneous electrical nerve stimulation on central pain modulation: a double-blind, placebo-controlled trial.

OBJECTIVES
Transcutaneous electrical nerve stimulation (TENS) is an analgesic current that is used in many acute and chronic painful states. The aim of this study was to investigate central pain modulation by low-frequency TENS.


METHODS
Twenty patients diagnosed with subacromial impingement syndrome of the shoulder were enrolled in the study. Patients were randomized into 2 groups: low-frequency TENS and sham TENS. Painful stimuli were delivered during which functional magnetic resonance imaging scans were performed, both before and after treatment. Ten central regions of interest that were reported to have a role in pain perception were chosen and analyzed bilaterally on functional magnetic resonance images. Perceived pain intensity during painful stimuli was evaluated using visual analog scale (VAS).


RESULTS
In the low-frequency TENS group, there was a statistically significant decrease in the perceived pain intensity and pain-specific activation of the contralateral primary sensory cortex, bilateral caudal anterior cingulate cortex, and of the ipsilateral supplementary motor area. There was a statistically significant correlation between the change of VAS value and the change of activity in the contralateral thalamus, prefrontal cortex, and the ipsilateral posterior parietal cortex. In the sham TENS group, there was no significant change in VAS value and activity of regions of interest.


DISCUSSION
We suggest that a 1-session low-frequency TENS may induce analgesic effect through modulation of discriminative, affective, and motor aspects of central pain perception.
[Multiple medication use in diabetic patients aged].

BACKGROUND
Multiple medication use is especially common in those with diabetes aged due to multiple illnesses, certain chronic diseases and disabling of the growing demand for care, treatment advances, but also some over-prescription.


AIMS
To assess the achievement of treatment goals in a population of older diabetics, to analyze drug consumption and to derive a practical driving prevention.


METHODS
This descriptive retrospective study was interested in 600 cases of diabetic patients older than 60 years, recruited from the diabetes followed at the National Institute of Nutrition and Health Unit in Tunis Sidi Hassine involving three local clinics to during the years 2009-2010.


RESULTS
The average age of the study population was 70 ± 0.5 years with extremes from 65 to 92 years. In our study, 91% of patients between 2 and 5 chronic diseases and the majority of subjects suffering from disabilities. The number of drugs prescribed in our subjects (all dosage forms combined) varies between 1 and 4,with a peak of interest to patients treated with 2-4 drugs, encountered in 91% of cases.The similarity of shapes and colors of certain drugs often confusing.


CONCLUSION
Multiple medication use is common in older diabetic subjects. Hence the need for good coordination between prescribers to prevent abuse and ensure the correct therapeutic education of patients and their families.
Physics-Based and Human-Derived Information Fusion Video Activity Analysis

With ubiquitous data acquired from sensors, there is an ever increasing ability to abstract content from the combination of physics-based and human-derived information fusion (PHIF). The advancement of PHIF tools include graphical information fusion methods, target tracking techniques, and natural language understanding. Current discussions revolve around dynamic data-driven applications systems (DDDAS) which seeks to leverage high-dimensional modeling with real-time physical systems. An example of a model includes a learned dictionary that can be leveraged as information queries. In this paper, we discuss the DDDAS paradigm of sensor measurements, information processing, environmental modeling, and software implementation to deliver content for PHIF systems. Experimental results demonstrate the DDDAS-based Live Video Computing DataBase Modeling Systems (LVC-DBMS) approach affording data discovery and query-based flexibility for awareness to provide narratives of unknown situations.
Involuntary paretic wrist/finger flexion forces and EMG increase with shoulder abduction load in individuals with chronic stroke

OBJECTIVE
Clinical observations of the flexion synergy in individuals with chronic hemiparetic stroke describe coupling of shoulder, elbow, wrist, and finger joints. Yet, experimental quantification of the synergy within a shoulder abduction (SABD) loading paradigm has focused only on shoulder and elbow joints. The paretic wrist and fingers have typically been studied in isolation. Therefore, this study quantified involuntary behavior of paretic wrist and fingers during concurrent activation of shoulder and elbow.


METHODS
Eight individuals with chronic moderate-to-severe hemiparesis and four controls participated. Isometric wrist/finger and thumb flexion forces and wrist/finger flexor and extensor electromyograms (EMG) were measured at two positions when lifting the arm: in front of the torso and at maximal reaching distance. The task was completed in the ACT(3D) robotic device with six SABD loads by paretic, non-paretic, and control limbs.


RESULTS
Considerable forces and EMG were generated during lifting of the paretic arm only, and they progressively increased with SABD load. Additionally, the forces were greater at the maximal reach position than at the position front of the torso.


CONCLUSIONS
Flexion of paretic wrist and fingers is involuntarily coupled with certain shoulder and elbow movements.


SIGNIFICANCE
Activation of the proximal upper limb must be considered when seeking to understand, rehabilitate, or develop devices to assist the paretic hand.