nils-herrmann/clean_scirepeval huggingface dataset:
What is cognitive reserve? Theory and research application of the reserve concept.

The idea of reserve against brain damage stems from the repeated observation that there does not appear to be a direct relationship between the degree of brain pathology or brain damage and the clinical manifestation of that damage. This paper attempts to develop a coherent theoretical account of reserve. One convenient subdivision of reserve models revolves around whether they envision reserve as a passive process, such as in brain reserve or threshold, or see the brain as actively attempting to cope with or compensate for pathology, as in cognitive reserve. Cognitive reserve may be based on more efficient utilization of brain networks or of enhanced ability to recruit alternate brain networks as needed. A distinction is suggested between reserve, the ability to optimize or maximize normal performance, and compensation, an attempt to maximize performance in the face of brain damage by using brain structures or networks not engaged when the brain is not damaged. Epidemiologic and imaging data that help to develop and support the concept of reserve are presented.
A Cluster-then-label Semi-supervised Learning Approach for Pathology Image Classification

Completely labeled pathology datasets are often challenging and time-consuming to obtain. Semi-supervised learning (SSL) methods are able to learn from fewer labeled data points with the help of a large number of unlabeled data points. In this paper, we investigated the possibility of using clustering analysis to identify the underlying structure of the data space for SSL. A cluster-then-label method was proposed to identify high-density regions in the data space which were then used to help a supervised SVM in finding the decision boundary. We have compared our method with other supervised and semi-supervised state-of-the-art techniques using two different classification tasks applied to breast pathology datasets. We found that compared with other state-of-the-art supervised and semi-supervised methods, our SSL method is able to improve classification performance when a limited number of labeled data instances are made available. We also showed that it is important to examine the underlying distribution of the data space before applying SSL techniques to ensure semi-supervised learning assumptions are not violated by the data.
Experimental security surveillance system for an Island-based facility

A test bed was developed for Plum Island, NY experimental multi-sensor security surveillance. The system includes broadband radars, cameras, an Automatic Identification System receiver, geophones and underwater passive acoustic sensors. The sensors were grouped into nodes connected to a Command and Control Center via a Wi-Fi network. Some sensors are COTS, some were developed and built by Stevens Institute of Technology. Sensor network was tested for the detection of potential surface and underwater intruders. This paper presents a system description and sensor performance estimations for various targets, including jet skis, small boats, kayaks, and divers. The system design performance versus cost considerations and methods of sensor integration are discussed.
Human action recognition using star skeleton

This paper presents a HMM-based methodology for action recogni-tion using star skeleton as a representative descriptor of human posture. Star skeleton is a fast skeletonization technique by connecting from centroid of target object to contour extremes. To use star skeleton as feature for action recognition, we clearly define the fea-ture as a five-dimensional vector in star fashion because the head and four limbs are usually local extremes of human shape. In our proposed method, an action is composed of a series of star skeletons over time. Therefore, time-sequential images expressing human action are transformed into a feature vector sequence. Then the fea-ture vector sequence must be transformed into symbol sequence so that HMM can model the action. We design a posture codebook, which contains representative star skeletons of each action type and define a star distance to measure the similarity between feature vec-tors. Each feature vector of the sequence is matched against the codebook and is assigned to the symbol that is most similar. Conse-quently, the time-sequential images are converted to a symbol posture sequence. We use HMMs to model each action types to be recognized. In the training phase, the model parameters of the HMM of each category are optimized so as to best describe the training symbol sequences. For human action recognition, the model which best matches the observed symbol sequence is selected as the recog-nized category. We implement a system to automatically recognize ten different types of actions, and the system has been tested on real human action videos in two cases. One case is the classification of 100 video clips, each containing a single action type. A 98% recog-nition rate is obtained. The other case is a more realistic situation in which human takes a series of actions combined. An action-series recognition is achieved by referring a period of posture history using a sliding window scheme. The experimental results show promising performance.
A 40 Gbps optical receiver analog front-end in 65 nm CMOS

A 40 Gbps optical receiver analog front end integrating a trans-impedance amplifier (TIA) and a limiting amplifier is presented. To achieve wide band operation, nested feedback TIA and interleaving post amplifier with split series-peaking are proposed in this design. This receiver provides the transimpedance of 92 dBOhm, input-referred noise of 14 pA/√Hz, −3dB bandwidth of 35 GHz, and 800mVpp differential output voltage swing. The total power dissipation is 168 mW from 1.2-V supply. Fabricated in a 65 nm CMOS technology, the chip size is 0.825mm2.
Modelling and Evaluating the Reliability of Distribution Systems

Comparatively, distribution systems have received least consideration in the reliability evaluation of power systems although paradoxically they have the greatest average effect on loss of supply to the consumers. This paper discusses the inherent features of typical distribution systems and describes and evaluates models that more truly reflect the operational behaviour of such systems and their effect on the consumers. The analysis of a typical system is included which illustrates the additional and more meaningful results that can be achieved from the use of these improved system models.
Deciphering Signatures of Mutational Processes Operative in Human Cancer

The genome of a cancer cell carries somatic mutations that are the cumulative consequences of the DNA damage and repair processes operative during the cellular lineage between the fertilized egg and the cancer cell. Remarkably, these mutational processes are poorly characterized. Global sequencing initiatives are yielding catalogs of somatic mutations from thousands of cancers, thus providing the unique opportunity to decipher the signatures of mutational processes operative in human cancer. However, until now there have been no theoretical models describing the signatures of mutational processes operative in cancer genomes and no systematic computational approaches are available to decipher these mutational signatures. Here, by modeling mutational processes as a blind source separation problem, we introduce a computational framework that effectively addresses these questions. Our approach provides a basis for characterizing mutational signatures from cancer-derived somatic mutational catalogs, paving the way to insights into the pathogenetic mechanism underlying all cancers.
Religious affiliation and suicide attempt.

Few studies have investigated the association between religion and suicide either in terms of Durkheim's social integration hypothesis or the hypothesis of the regulative benefits of religion. The relationship between religion and suicide attempts has received even less attention.



Depressed inpatients (N=371) who reported belonging to one specific religion or described themselves as having no religious affiliation were compared in terms of their demographic and clinical characteristics.



Religiously unaffiliated subjects had significantly more lifetime suicide attempts and more first-degree relatives who committed suicide than subjects who endorsed a religious affiliation. Unaffiliated subjects were younger, less often married, less often had children, and had less contact with family members. Furthermore, subjects with no religious affiliation perceived fewer reasons for living, particularly fewer moral objections to suicide. In terms of clinical characteristics, religiously unaffiliated subjects had more lifetime impulsivity, aggression, and past substance use disorder. No differences in the level of subjective and objective depression, hopelessness, or stressful life events were found.



Religious affiliation is associated with less suicidal behavior in depressed inpatients. After other factors were controlled, it was found that greater moral objections to suicide and lower aggression level in religiously affiliated subjects may function as protective factors against suicide attempts. Further study about the influence of religious affiliation on aggressive behavior and how moral objections can reduce the probability of acting on suicidal thoughts may offer new therapeutic strategies in suicide prevention.
The Design and Experiment of a Dual-band Omni-directional SIW Slot Array Antenna

In this paper, a new structure is proposed to implement dual-band SIW slot array omni-directional antennas. The desired radiation patterns of the two bands can be almost achieved independently due to the weak coupling between the slots for different frequency bands. A dual-band omni-directional antenna for 2.4GHz and 3.5GHz is designed and fabricated on a low loss dielectric substrate with normal printed circuit board (PCB) process, the measured results show that moderate impedance bandwidths and good omni-directional radiation patterns at both bands are achieved.
Cognitive Work Analysis Toward Safe, Productive, and Healthy Computer-Based Work [Book Review]

Book Publisher: Mahwah,  Lawrence Erlbaum Associates, 1999, 392 pp. with index and references. This book is already the classic text in the area of cognitive work analysis (CWA), and the author, Kim Vicente, is a recognized expert in the field. CWA is an approach to the problem of understanding the work required to perform complex tasks. The approach was developed at the Ris National Laboratory in Roskilde, Denmark, under the leadership of Jens Rasmussen, head of the electronics department.
Gleaner: Creating ensembles of first-order clauses to improve recall-precision curves

Many domains in the field of Inductive Logic Programming (ILP) involve highly unbalanced data. A common way to measure performance in these domains is to use precision and recall instead of simply using accuracy. The goal of our research is to find new approaches within ILP particularly suited for large, highly-skewed domains. We propose Gleaner, a randomized search method that collects good clauses from a broad spectrum of points along the recall dimension in recall-precision curves and employs an “at least L of these K clauses” thresholding method to combine sets of selected clauses. Our research focuses on Multi-Slot Information Extraction (IE), a task that typically involves many more negative examples than positive examples. We formulate this problem into a relational domain, using two large testbeds involving the extraction of important relations from the abstracts of biomedical journal articles. We compare Gleaner to ensembles of standard theories learned by Aleph, finding that Gleaner produces comparable testset results in a fraction of the training time.
Side-Channel Analysis of Cryptographic RFIDs with Analog Demodulation

As most modern cryptographic Radio Frequency Identification (RFID) devices are based on ciphers that are secure from a purely theoretical point of view, e.g., (Triple-)DES or AES, adversaries have been adopting new methods to extract secret information and cryptographic keys from contactless smartcards: Side-Channel Analysis (SCA) targets the physical implementation of a cipher and allows to recover secret keys by exploiting a side-channel, for instance, the electro-magnetic (EM) emanation of an Integrated Circuit (IC). In this paper we present an analog demodulator specifically designed for refining the SCA of contactless smartcards. The customized analogue hardware increases the quality of EM measurements, facilitates the processing of the side-channel leakage and can serve as a plug-in component to enhance any existing SCA laboratory. Employing it to obtain power profiles of several real-world cryptographic RFIDs, we demonstrate the effectiveness of our measurement setup and evaluate the improvement of our new analog technique compared to previously proposed approaches. Using the example of the popular Mifare DESFire MF3ICD40 contactless smartcard, we show that commercial RFID devices are susceptible to the proposed SCA methods. The security analyses presented in this paper do not require expensive equipment and demonstrate that SCA poses a severe threat to many real-world systems. This novel attack vector has to be taken into account when employing contactless smartcards in security-sensitive applications, e.g., for wireless payment or identification.
Evaluation of prediction strategy and care coordination for COPD readmissions.

Factors that influence the likelihood of readmission for chronic obstructive pulmonary disease (COPD) patients and the impact of posthospital care coordination remain uncertain. LACE index (L = length of stay, A = Acuity of admission; C = Charlson comorbidity index; E = No. of emergency department (ED) visits in last 6 months) is a validated tool for predicting 30-days readmissions for general medicine patients. We aimed to identify variables predictive of COPD readmissions including LACE index and determine the impact of a novel care management process on 30-day all-cause readmission rate.



In a case-control design, potential readmission predictors including LACE index were analyzed using multivariable logistic regression for 461 COPD patients between January-October 2013. Patients with a high LACE index at discharge began receiving care coordination in July 2013. We tested for association between readmission and receipt of care coordination between July-October 2013. Care coordination consists of a telephone call from the care manager who: 1) reviews discharge instructions and medication reconciliation; 2) emphasizes importance of medication adherence; 3) makes a follow-up appointment with primary care physician within 1-2 weeks and; 4) makes an emergency back-up plan.



COPD readmission rate was 16.5%. An adjusted LACE index of ≥ 13 was not associated with readmission (p = 0.186). Significant predictors included female gender (odds ratio [OR] 0.51, 95% confidence interval [CI] 0.29-0.91, p = 0.021); discharge to skilled nursing facility (OR 3.03, 95% CI 1.36-6.75, p = 0.007); 4-6 comorbid illnesses (OR 9.21, 95% CI 1.17-76.62, p = 0.035) and ≥ 4 ED visits in previous 6 months (OR 6.40, 95% CI 1.25-32.87, p = 0.026). Out of 119 patients discharged between July-October 2013, 41% received the care coordination. The readmission rate in the intervention group was 14.3% compared to 18.6% in controls (p = 0.62).



Factors influencing COPD readmissions are complex and poorly understood. LACE index did not predict 30-days all-cause COPD readmissions. Posthospital care coordination for transition of care from hospital to the community showed a 4.3% reduction in the 30-days all-cause readmission rate which did not reach statistical significance (p = 0.62).
Mobile.net: Mobile Telephone Text Messages to Encourage Adherence to Medication and to Follow up With People With Psychosis: Methods and Protocol for a Multicenter Randomized Controlled Two-Armed Trial

Schizophrenia is a high-cost, chronic, serious mental illness. There is a clear need to improve treatments and expand access to care for persons with schizophrenia, but simple, tailored interventions are missing.



To evaluate the impact of tailored mobile telephone text messages to encourage adherence to medication and to follow up with people with psychosis at 12 months.



Mobile.Net is a pragmatic randomized trial with inpatient psychiatric wards allocated to two parallel arms. The trial will include 24 sites and 45 psychiatric hospital wards providing inpatient care in Finland. The participants will be adult patients aged 18-65 years, of either sex, with antipsychotic medication (Anatomical Therapeutic Chemical classification 2011) on discharge from a psychiatric hospital, who have a mobile phone, are able to use the Finnish language, and are able to give written informed consent to participate in the study. The intervention group will receive semiautomatic system (short message service [SMS]) messages after they have been discharged from the psychiatric hospital. Patients will choose the form, content, timing, and frequency of the SMS messages related to their medication, keeping appointments, and other daily care. SMS messages will continue to the end of the study period (12 months) or until participants no longer want to receive the messages. Patients will be encouraged to contact researchers if they feel that they need to adjust the message in any way. At all times, both groups will receive usual care at the discretion of their team (psychiatry and nursing). The primary outcomes are service use and healthy days by 12 months based on routine data (admission to a psychiatric hospital, time to next hospitalization, time in hospital during this year, and healthy days). The secondary outcomes are service use, coercive measures, medication, adverse events, satisfaction with care, the intervention, and the trial, social functioning, and economic factors. Data will be collected 12 months after baseline. The outcomes are based on the national health registers and patients' subjective evaluations. The primary analysis will be by intention-to-treat.
Memory formation depends on both synapse-specific modifications of synaptic strength and cell-specific increases in excitability

The modification of synaptic strength produced by long-term potentiation (LTP) is widely thought to underlie memory storage. Indeed, given that hippocampal pyramidal neurons have >10,000 independently modifiable synapses, the potential for information storage by synaptic modification is enormous. However, recent work suggests that CREB-mediated global changes in neuronal excitability also play a critical role in memory formation. Because these global changes have a modest capacity for information storage compared with that of synaptic plasticity, their importance for memory function has been unclear. Here we review the newly emerging evidence for CREB-dependent control of excitability and discuss two possible mechanisms. First, the CREB-dependent transient change in neuronal excitability performs a memory-allocation function ensuring that memory is stored in ways that facilitate effective linking of events with temporal proximity (hours). Second, these changes may promote cell-assembly formation during the memory-consolidation phase. It has been unclear whether such global excitability changes and local synaptic mechanisms are complementary. Here we argue that the two mechanisms can work together to promote useful memory function. The authors discuss newly emerging evidence for the role of the transcription factor CREB in memory, including its role in modulating changes in excitability that are critical for neural assembly formation and linking of memories across time.
An Empirical Comparison of Human Value Models

Over the past century, various value models have been proposed. To determine which value model best predicts prosocial behavior, mental health, and pro-environmental behavior, we subjected seven value models to a hierarchical regression analysis. A sample of University students (N = 271) completed the Portrait Value Questionnaire (Schwartz et al., 2012), the Basic Value Survey (Gouveia et al., 2008), and the Social Value Orientation scale (Van Lange et al., 1997). Additionally, they completed the Values Survey Module (Hofstede and Minkov, 2013), Inglehart's (1977) materialism-postmaterialism items, the Study of Values, fourth edition (Allport et al., 1960; Kopelman et al., 2003), and the Rokeach (1973) Value Survey. However, because the reliability of the latter measures was low, only the PVQ-RR, the BVS, and the SVO where entered into our analysis. Our results provide empirical evidence that the PVQ-RR is the strongest predictor of all three outcome variables, explaining variance above and beyond the other two instruments in almost all cases. The BVS significantly predicted prosocial and pro-environmental behavior, while the SVO only explained variance in pro-environmental behavior.
Holmium laser ablation of the prostate (HoLAP): intermediate-term results of 144 patients

To retrospectively analyse the intermediate-term outcome of holmium laser ablation of the prostate (HoLAP) of up to 4 years postoperatively in one of the largest series and to define the selection criteria for patients who benefit from potentially lower complications associated with HoLAP. Between June 2006 and November 2010, 144 patients with benign prostatic obstruction were treated at two centres with standardised HoLAP (2.0 J/50 Hz or 3.2 J/25 Hz with Versapulse® 80–100 W laser Lumenis®). Median follow-up was 21 months (range, 1–54). International prostate symptom score and quality of life (IPSS-QoL), PSA, prostate volume, maximal flow rate (Qmax), postvoiding residual volume (Vres) were evaluated pre- and postoperatively. All complications were graded according to CTCAE (v4.03). Mean patient age was 70.1 ± 7.7 years (range, 46–90). With a preoperative median prostate volume of 40 ml (range, 10–130), the median operation time was 50 min (range, 9–138). We observed a median catheterisation time of 1 day (range, 0–12) and hospitalisation time of 2 days (range, 1–16). IPSS-QoL, Qmax and Vres were significantly improved after 3 months, and all parameters remained unchanged after 12, 24 and 36 months. The rate of re-operation was significantly lower in patients with prostate volume <40 ml, compared to patients with prostates ≥40 ml (9.1 vs. 25 %, p = 0.04). HoLAP is a safe and effective procedure for the treatment of prostates <40 ml. Patients benefit from HoLAP because of a low bleeding rate and short hospital stay. Due to high recurrence rates, HoLAP should be avoided in prostates >40 ml.
Autonomous exploration of mobile robots through deep neural networks

The exploration problem of mobile robots aims to allow mobile robots to explore an unknown environment. We describe an indoor exploration algorithm for mobile robots using a hierarchical structure that fuses several convolutional neural network layers with the decision-making process. The whole system is trained end to end by taking only visual information (RGB+D information) as input and generates a sequence of main moving direction as output so that the robot achieves autonomous exploration ability. The robot is a Turtlebot with a Kinect mounted on it. The model is trained and tested in a real world environment. And the training dataset is provided for download. The outputs of the test date are compared with the human decision. We use Gaussian process latent variable model to visualize the feature map of last convolutional layer and it proves the effectiveness of this deep convolution neural network model. we also present a novel and lightweight deep-learning library libcnn especially for deep-learning processing of robotics tasks.