LLukas22/scidocs huggingface dataset:
Maternal-Preterm Skin-to-Skin Contact Enhances Child Physiologic Organization and Cognitive Control Across the First 10 Years of Life

BACKGROUND
Maternal-newborn contact enhances organization of the infant's physiological systems, including stress reactivity, autonomic functioning, and sleep patterns, and supports maturation of the prefrontal cortex and its ensuing effects on cognitive and behavioral control. Premature birth disrupts brain development and is associated with maternal separation and disturbances of contact-sensitive systems. However, it is unknown whether the provision of maternal-preterm contact can improve long-term functioning of these systems.


METHODS
We used the Kangaroo Care (KC) intervention and provided maternal-newborn skin-to-skin contact to 73 premature infants for 14 consecutive days compared with 73 case-matched control subjects receiving standard incubator care. Children were then followed seven times across the first decade of life and multiple physiologic, cognitive, parental mental health, and mother-child relational measures were assessed.


RESULTS
KC increased autonomic functioning (respiratory sinus arrhythmia, RSA) and maternal attachment behavior in the postpartum period, reduced maternal anxiety, and enhanced child cognitive development and executive functions from 6 months to 10 years. By 10 years of age, children receiving KC showed attenuated stress response, improved RSA, organized sleep, and better cognitive control. RSA and maternal behavior were dynamically interrelated over time, leading to improved physiology, executive functions, and mother-child reciprocity at 10 years.


CONCLUSIONS
These findings are the first to demonstrate long-term effects of early touch-based intervention on children's physiologic organization and behavioral control and have salient implications for the care practices of premature infants. Results demonstrate the dynamic cascades of child physiological regulation and parental provisions in shaping developmental outcome and may inform the construction of more targeted early interventions.
Context aware 3D gesture recognition for games and virtual reality

classroom use is granted without fee provided that copies are not made or distributed for commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for third-party components of this work must be honored. For all other uses, contact the Owner/Author. Copyright is held by the owner/author(s). SIGGRAPH 2015 Courses, August 09 – 13, 2015, Los Angeles, CA. ACM 978-1-4503-3634-5/15/08. Context Aware 3D Gesture Recognition for Games and Virtual Reality
Constructing Bayesian networks for criminal profiling from limited data

The increased availability of information technologies has enabled law enforcement agencies to compile databases with detailed information about major felonies. Machine learning techniques can utilize these databases to produce decision-aid tools to support police investigations. This paper presents a methodology for obtaining a Bayesian network (BN) model of offender behavior from a database of cleared homicides. The BN can infer the characteristics of an unknown offender from the crime scene evidence, and help narrow the list of suspects in an unsolved homicide. Our research shows that 80% of offender characteristics are predicted correctly on average in new single-victim homicides, and when confidence levels are taken into account this accuracy increases to 95.6%. 2008 Elsevier B.V. All rights reserved.
Exploring consumer adoption of new services by analyzing the behavior of 3G subscribers: An empirical case study

As the profit margins of 3G mobile network operators gradually decline, and market competition becomes increasingly intensive, they must develop rich and diverse varieties of brand new application services to attract new subscribers and retain old ones. Understanding the customer’s purchasing behavior is a key issue in this process. The operator must accurately grasp movements in the market based on analysis of the behavior of 3G subscribers. This study proposes a comprehensive customer relationship management strategy framework to furnish a beneficial plan to overcome such challenges. First, we propose a new model to identify who are the high-value customers related to the characteristics of new telecommunication services. After segmenting the customers, we propose a procedure to provide different kinds of usage analysis, including inter-cluster analysis and intra-cluster analysis. The experimental results are determined based on rules extracted from a large number of call detail records generated by the mobile subscribers of leading 3G mobile system operators in Taiwan. The dependency network demonstrates the relationship between voice services, data communications, message services, micropayments and entertainment. Finally, we propose some marketing recommendations for 3G system operators based on these interesting rules. 2011 Elsevier B.V. All rights reserved.
Sowing the Seeds for a more Creative Society

Unfortunately, few of today’s classrooms focus on helping students develop as creative thinkers. Even students who perform well in school are often unprepared for the challenges that they encounter after graduation, in their work lives as well as their personal lives. Many students learn to solve specific types of problems, but they are unable to adapt and improvise in response to the unexpected situations that inevitably arise in today’s fast-changing world.
Scaling the h-index for different scientific ISI fields

We propose a simple way to put in a common scale the h values of researchers working in different scientific ISI fields, so that the foreseeable misuse of this index for inter-areas comparison might be prevented, or at least, alleviated.
Towards a taxonomy of software change

Previous taxonomies of software change have focused on the purpose of the change (i.e., the why) rather than the underlying mechanisms. This paper proposes a taxonomy of software change based on characterizing the mechanisms of change and the factors that influence these mechanisms. The ultimate goal of this taxonomy is to provide a framework that positions concrete tools, formalisms and methods within the domain of software evolution. Such a framework would considerably ease comparison between the various mechanisms of change. It would also allow practitioners to identify and evaluate the relevant tools, methods and formalisms for a particular change scenario. As an initial step towards this taxonomy, the paper presents a framework that can be used to characterize software change support tools and to identify the factors that impact on the use of these tools. The framework is evaluated by applying it to three different change support tools and by comparing these tools based on this analysis. Copyright c © 2005 John Wiley & Sons, Ltd.
Promise and Pitfalls of Terrorism Research

Using a database of recent articles published in prominent political science journals, we show the rapid increase in terrorism research. Given this increased awareness and attention, we identify several problems that still plague the study of political terrorism including definitional problems that lack empirical tests, not distinguishing among different types of terrorism, and using the wrong unit of analysis when designing research. After identifying these problems—especially as they relate to the quantitative study of terrorism—we suggest some solutions. We then apply these suggestions to investigate whether changing the definition of terrorism, different types of terrorism, or changing the unit of analysis affects key predictors of terror events cross-nationally. One of our tests consists of varying the unit of observation to include directed dyads, which offers the potential to test some of the many strategic models of terrorism. Our analysis suggests that varying definitions of terrorism, such as military vs. non-military targets, might not be that consequential, whereas different types of terrorism, such as domestic vs. transnational, could be driven by fundamentally different processes. We also conclude that modeling transnational terrorism differently using directed dyads yields new and interesting insights into the process of terrorism.
Forensic data acquisition from cloud-of-things devices: windows Smartphones as a case study

The continued amalgamation of cloud technologies into all aspects of our daily lives and the technologies we use (i.e. cloud-of-things) creates business opportunities, security and privacy risks, and investigative challenges (in the event of a cybersecurity incident). This study examines the extent to which data acquisition fromWindows phone, a common cloud-of-thing device, is supported by three popular mobile forensics tools. The effect of device settings modification (i.e. enabling screen lock and device reset operations) and alternative acquisition processes (i.e. individual and combined acquisition) on the extraction results are also examined. Our results show that current mobile forensic tool support for Windows Phone 8 remains limited. The results also showed that logical acquisition support was more complete in comparison to physical acquisition support. In one example, the tool was able to complete a physical acquisition of a Nokia Lumia 625, but its deleted contacts and SMSs could not be recovered/extracted. In addition we found that separate acquisition is needed for device removable media to maximize acquisition results, particularly when trying to recover deleted data. Furthermore, enabling flight-mode and disabling location services are highly recommended to eliminate the potential for data alteration during the acquisition process. These results should provide practitioners with an overview of the current capability of mobile forensic tools and the challenges in successfully extracting evidence from the Windows phone platform. Copyright © 2016 John Wiley & Sons, Ltd.
Machine Learning-Assisted Optical Performance Monitoring in Fiber-Optic Networks

We review machine learning (ML)-based optical performance monitoring (OPM) techniques in optical communications. Recent applications of ML-assisted OPM in different aspects of fiber-optic networking including cognitive fault detection and management, network equipment failure prediction, and dynamic planning and optimization of software-defined networks are also discussed.
Sjogren’s syndrome: Review of the aetiology, 
Pathophysiology & Potential therapeutic interventions

BACKGROUND
Sjogren's syndrome (SS) is an autoimmune disorder characterised by lymphocytic infiltration of exocrine glands, resulting in glandular dysfunction. Objectives: This study aims to review the aetiology of Sjogren's syndrome, highlight aspects that contribute to the pathophysiology of the disease and explore treatment options that target different mediators of pathogenesis.


MATERIAL AND METHODS
The MEDLINE/PubMed and Google Scholar databases were searched systematically with the terms "Sjogren's syndrome"; "clinical"; "treatment"; "management". Eligible studies had to meet a predefined inclusion criteria.


RESULTS
912 identified studies were evaluated against the inclusion criteria. 25 eligible studies were included for review. Sjogren's syndrome is a multifactorial condition with genetic, environmental and hormonal factors playing a role in establishing the condition. B-cell activating factor (BAFF) is an important mediator in the induction and perpetuation of this condition. Elevated BAFF levels, found in patients with SS, promote growth of B-cells and subsequent production of autoantibody; anti-SSA/Ro. BAFF inhibitors are important potential therapeutic drugs that may be effective in patients with Sjogren's syndrome. Other potential targets include CD20 and CD22 that cause B-cell depletion.


CONCLUSIONS
The pathophysiology of this exocrinopathy has not fully been elucidated. Potential therapeutic interventions include BAFF inhibitors and anti-CD20 and anti-CD22 therapy. However, no clinical trials have been conducted on subjects with Sjogren's syndrome to support existing research. Key words:Sjogren's syndrome, autoimmune, rheumatology.
Schizophrenia: a five-year follow-up of patient outcome following psycho-education for caregivers.

INTRODUCTION
There is evidence that psycho-education courses for caregivers of individuals with schizophrenia improve the short-term outcome of the condition. However, most of the outcome studies are limited to two-year follow-up.


MATERIALS AND METHODS
This study is a five-year retrospective case-control follow-up of an original cohort of 63 patients and their 101 caregivers who completed a six-week Caregiver Psycho-education Programme (CPP) for schizophrenia and psychosis between 2002 and 2005, and 60 controls, matched for age, gender and severity of their psychotic illness.


RESULTS
Patients whose caregivers learned more from the six-week psycho-education course had a significantly longer time to relapse (P = 0.04) and a significantly shorter length of stay during their first relapse (P < 0.05). Patients whose caregivers attended the six-week psycho-education course (regardless of how much the caregivers learned) had a significantly better outcome than controls. This included a significantly smaller number of relapses (P < 0.01), longer time to relapse (P < 0.01), shorter length of stay during their first relapse (P < 0.01) and smaller number of bed days over five years (P < 0.01). The odds ratio of controls relapsing, although insignificant at one year, was 4.13 (1.85-9.21) at five years. Outcome was not affected by either the numbers of caregivers attending for each patient, or caregiver gender.


DISCUSSION AND CONCLUSIONS
This study, which is among the first to examine outcome over five years, supports the efficacy of psycho-education for caregivers in improving outcome for patients. Caregivers should be encouraged to take up psycho-education where it is available.
Exploring the Usability of Augmented Reality Interaction Techniques During Children's Early Elementary-School Years

over concrete thinking Understand that virtual objects are computer generated, and they do not need to obey physical laws
Algorithmically Generated Domain Detection and Malware Family Classification

In this paper, we compare the performance of several machine learning based approaches for the tasks of detecting algorithmically generated malicious domains and the categorization of domains according to their malware family. The datasets used for model comparison were provided by the shared task on Detecting Malicious Domain names (DMD 2018). Our models ranked first for two out of the four test datasets provided in the competition.
Induced Systemic Resistance and Promotion of Plant Growth by Bacillus spp.

ABSTRACT Elicitation of induced systemic resistance (ISR) by plant-associated bacteria was initially demonstrated using Pseudomonas spp. and other gram-negative bacteria. Several reviews have summarized various aspects of the large volume of literature on Pseudomonas spp. as elicitors of ISR. Fewer published accounts of ISR by Bacillus spp. are available, and we review this literature for the first time. Published results are summarized showing that specific strains of the species B. amyloliquefaciens, B. subtilis, B. pasteurii, B. cereus, B. pumilus, B. mycoides, and B. sphaericus elicit significant reductions in the incidence or severity of various diseases on a diversity of hosts. Elicitation of ISR by these strains has been demonstrated in greenhouse or field trials on tomato, bell pepper, muskmelon, watermelon, sugar beet, tobacco, Arabidopsis sp., cucumber, loblolly pine, and two tropical crops (long cayenne pepper and green kuang futsoi). Protection resulting from ISR elicited by Bacillus spp. has been reported against leaf-spotting fungal and bacterial pathogens, systemic viruses, a crown-rotting fungal pathogen, root-knot nematodes, and a stem-blight fungal pathogen as well as damping-off, blue mold, and late blight diseases. Reductions in populations of three insect vectors have also been noted in the field: striped and spotted cucumber beetles that transmit cucurbit wilt disease and the silver leaf whitefly that transmits Tomato mottle virus. In most cases, Bacillus spp. that elicit ISR also elicit plant growth promotion. Studies on mechanisms indicate that elicitation of ISR by Bacillus spp. is associated with ultrastructural changes in plants during pathogen attack and with cytochemical alterations. Investigations into the signal transduction pathways of elicited plants suggest that Bacillus spp. activate some of the same pathways as Pseudomonas spp. and some additional pathways. For example, ISR elicited by several strains of Bacillus spp. is independent of salicylic acid but dependent on jasmonic acid, ethylene, and the regulatory gene NPR1-results that are in agreement with the model for ISR elicited by Pseudomonas spp. However, in other cases, ISR elicited by Bacillus spp. is dependent on salicylic acid and independent of jasmonic acid and NPR1. In addition, while ISR by Pseudomonas spp. does not lead to accumulation of the defense gene PR1 in plants, in some cases, ISR by Bacillus spp. does. Based on the strains and results summarized in this review, two products for commercial agriculture have been developed, one aimed mainly at plant growth promotion for transplanted vegetables and one, which has received registration from the U.S. Environmental Protection Agency, for disease protection on soybean.
Accuracy of Kinematic Positioning Using Global Satellite Navigation Systems under Forest Canopies

A harvester enables detailed roundwood data to be collected during harvesting operations by means of the measurement apparatus integrated into its felling head. These data can be used to improve the efficiency of wood procurement and also replace some of the field measurements, and thus provide both less costly and more detailed ground truth for remote sensing based forest inventories. However, the positional accuracy of harvester-collected tree data is not sufficient currently to match the accuracy per individual trees achieved with remote sensing data. The aim in the present study was to test the accuracy of various instruments utilizing global satellite navigation systems (GNSS) in motion under forest canopies of varying densities to enable us to get an understanding of the current state-of-the-art in GNSS-based positioning under forest canopies. Tests were conducted using several different combinations of GNSS and inertial measurement unit (IMU) mounted OPEN ACCESS Forests 2015, 6 3219 on an all-terrain vehicle (ATV) “simulating” a moving harvester. The positions of 224 trees along the driving route were measured using a total-station and real-time kinematic GPS. These trees were used as reference items. The position of the ATV was obtained using GNSS and IMU with an accuracy of 0.7 m (root mean squared error (RMSE) for 2D positions). For the single-frequency GNSS receivers, the RMSE of real-time 2D GNSS positions was 4.2–9.3 m. Based on these results, it seems that the accuracy of novel single-frequency GNSS devices is not so dependent on forest conditions, whereas the performance of the tested geodetic dual-frequency receiver is very sensitive to the visibility of the satellites. When postprocessing can be applied, especially when combined with IMU data, the improvement in the accuracy of the dual-frequency receiver was significant.
Predictors of improvement and progression of diabetic polyneuropathy following treatment with α-lipoic acid for 4 years in the NATHAN 1 trial.

AIMS
We aimed to analyze the impact of baseline factors on the efficacy of α-lipoic acid (ALA) over 4 years in the NATHAN 1 trial.


METHODS
This was a post-hoc analysis of the NATHAN 1 trial, a 4-year randomized study including 460 diabetic patients with mild-to-moderate polyneuropathy using ALA 600 mg qd or placebo. Amongst others, efficacy measures were the Neuropathy Impairment Score of the lower limbs (NIS-LL) and heart rate during deep breathing (HRDB).


RESULTS
Improvement and prevention of progression of NIS-LL (ΔNIS-LL≥2 points) with ALA vs. placebo after 4 years was predicted by higher age, lower BMI, male sex, normal blood pressure, history of cardiovascular disease (CVD), insulin treatment, longer duration of diabetes and neuropathy, and higher neuropathy stage. Participants treated with ALA who received ACE inhibitors showed a better outcome in HRDB after 4 years.


CONCLUSIONS
Better outcome in neuropathic impairments following 4-year treatment with α-lipoic acid was predicted by normal BMI and blood pressure and higher burden due to CVD, diabetes, and neuropathy, while improvement in cardiac autonomic function was predicted by ACE inhibitor treatment. Thus, optimal control of CVD risk factors could contribute to improved efficacy of α-lipoic acid in patients with higher disease burden.
Single autologous stem-cell transplantation followed by maintenance therapy with thalidomide is superior to double autologous transplantation in multiple myeloma: results of a multicenter randomized clinical trial.

From April 2003 to December 2006, 195 patients with de novo symptomatic myeloma and younger than 60 years of age were randomly assigned to receive either tandem transplantation up front (arm A, n = 97) or one autologous stem-cell transplantation followed by a maintenance therapy with thalidomide (day + 90, 100 mg per day during 6 months) (arm B, n = 98). Patients included in arm B received a second transplant at disease progression. In both arms, autologous stem-cell transplantation was preceded by first-line therapy with thalidomide-dexamethasone and subsequent collection of peripheral blood stem cells with high-dose cyclophosphamide (4 g/m(2)) and granulocyte colony stimulating factor. Data were analyzed on an intent-to-treat basis. With a median follow-up of 33 months (range, 6-46 months), the 3-year overall survival was 65% in arm A and 85% in arm B (P = .04). The 3-year progression-free survival was 57% in arm A and 85% in arm B (P = .02). Up-front single autologous transplantation followed by 6 months of maintenance therapy with thalidomide (with second transplant in reserve for relapse or progression) is an effective therapeutic strategy to treat multiple myeloma patients and appears superior to tandem transplant in this setting. This study was registered at www.ClinicalTrials.gov as (NCT 00207805).
Image hash generation method using hierarchical histogram

Recently, web applications, such as Stock Image and Image Library, are developed to provide the integrated management for user's images. Image hashing techniques are used for the image registration, management and retrieval as the identifier also, investigations have been performed to raise the hash performance like discernment. This paper proposes GLOCAL image hashing method utilizing the hierarchical histogram which is based on histogram bin population method. So far, many studies have proven that image hashing techniques based on this histogram are robust against image processing and geometrical attacks. We modified existing image hashing method developed by our research team [20]. The main idea of the paper is that it helps generate more fluent hash string if we have specific length of histogram bin. Another operation is empowering weighting factor into hash string at each level. Thus, we can raise the magnitude of hash string generated from same context or features and also strengthen the robustness of generated hash.