LLukas22/scidocs huggingface dataset:
Growth rates of black soldier fly larvae fed on fresh human faeces and their implication for improving sanitation.

OBJECTIVES
To determine the capacity of black soldier fly larvae (BSFL) (Hermetia illucens) to convert fresh human faeces into larval biomass under different feeding regimes, and to determine how effective BSFL are as a means of human faecal waste management.


METHODS
Black soldier fly larvae were fed fresh human faeces. The frequency of feeding, number of larvae and feeding ratio were altered to determine their effects on larval growth, prepupal weight, waste reduction, bioconversion and feed conversion rate (FCR).


RESULTS
The larvae that were fed a single lump amount of faeces developed into significantly larger larvae and prepupae than those fed incrementally every 2 days; however, the development into pre-pupae took longer. The highest waste reduction was found in the group containing the most larvae, with no difference between feeding regimes. At an estimated 90% pupation rate, the highest bioconversion (16-22%) and lowest, most efficient FCR (2.0-3.3) occurred in groups that contained 10 and 100 larvae, when fed both the lump amount and incremental regime.


CONCLUSION
The prepupal weight, bioconversion and FCR results surpass those from previous studies into BSFL management of swine, chicken manure and municipal organic waste. This suggests that the use of BSFL could provide a solution to the health problems associated with poor sanitation and inadequate human waste management in developing countries.
Dynamic Access Control Policy based on Blockchain and Machine Learning for the Internet of Things

The Internet of Things (IoT) is now destroying the barriers between the real and digital worlds. However, one of the huge problems that can slow down the development of this global wave, or even stop it, concerns security and privacy requirements. The criticality of these latter comes especially from the fact that the smart objects may contain very intimate information or even may be responsible for protecting people’s lives. In this paper, the focus is on access control in the IoT context by proposing a dynamic and fully distributed security policy. Our proposal will be based, on one hand, on the concept of the blockchain to ensure the distributed aspect strongly recommended in the IoT; and on the other hand on machine learning algorithms, particularly on reinforcement learning category, in order to provide a dynamic, optimized and selfadjusted security policy. Keywords—Internet of Things; security; access control; dynamic policy; security policy; blockchain; machine learning; reinforcement learning
Validation of a new mass screening tool for cognitive impairment: Cognitive Assessment for Dementia, iPad version

BACKGROUND
We have developed a new screening test for dementia that runs on an iPad and can be used for mass screening, known as the Cognitive Assessment for Dementia, iPad version (CADi). The CADi consists of items involving immediate recognition memory for three words, semantic memory, categorization of six objects, subtraction, backward repetition of digits, cube rotation, pyramid rotation, trail making A, trail making B, and delayed recognition memory for three words. The present study examined the reliability and validity of the CADi.


METHODS
CADi evaluations were conducted for patients with dementia, healthy subjects selected from a brain checkup system, and community-dwelling elderly people participating in health checkups.


RESULTS
CADi scores were lower for dementia patients than for healthy elderly individuals and correlated significantly with Mini-Mental State Examination scores. Cronbach's alpha values for the CADi were acceptable (over 0.7), and test-retest reliability was confirmed via a significant correlation between scores separated by a one-year interval.


CONCLUSION
These results suggest that the CADi is a useful tool for mass screening of dementia in Japanese populations.
Dihydrofolate-Reductase Mutations in Plasmodium knowlesi Appear Unrelated to Selective Drug Pressure from Putative Human-To-Human Transmission in Sabah, Malaysia

BACKGROUND
Malaria caused by zoonotic Plasmodium knowlesi is an emerging threat in Eastern Malaysia. Despite demonstrated vector competency, it is unknown whether human-to-human (H-H) transmission is occurring naturally. We sought evidence of drug selection pressure from the antimalarial sulfadoxine-pyrimethamine (SP) as a potential marker of H-H transmission.


METHODS
The P. knowlesi dihdyrofolate-reductase (pkdhfr) gene was sequenced from 449 P. knowlesi malaria cases from Sabah (Malaysian Borneo) and genotypes evaluated for association with clinical and epidemiological factors. Homology modelling using the pvdhfr template was used to assess the effect of pkdhfr mutations on the pyrimethamine binding pocket.


RESULTS
Fourteen non-synonymous mutations were detected, with the most common being at codon T91P (10.2%) and R34L (10.0%), resulting in 21 different genotypes, including the wild-type, 14 single mutants, and six double mutants. One third of the P. knowlesi infections were with pkdhfr mutants; 145 (32%) patients had single mutants and 14 (3%) had double-mutants. In contrast, among the 47 P. falciparum isolates sequenced, three pfdhfr genotypes were found, with the double mutant 108N+59R being fixed and the triple mutants 108N+59R+51I and 108N+59R+164L occurring with frequencies of 4% and 8%, respectively. Two non-random spatio-temporal clusters were identified with pkdhfr genotypes. There was no association between pkdhfr mutations and hyperparasitaemia or malaria severity, both hypothesized to be indicators of H-H transmission. The orthologous loci associated with resistance in P. falciparum were not mutated in pkdhfr. Subsequent homology modelling of pkdhfr revealed gene loci 13, 53, 120, and 173 as being critical for pyrimethamine binding, however, there were no mutations at these sites among the 449 P. knowlesi isolates.


CONCLUSION
Although moderate diversity was observed in pkdhfr in Sabah, there was no evidence this reflected selective antifolate drug pressure in humans.
Cross-cultural Differences in Mental Health, Quality of Life, Empathy, and Burnout between US and Brazilian Medical Students.

OBJECTIVE
This study aimed to compare mental health, quality of life, empathy, and burnout in medical students from a medical institution in the USA and another one in Brazil.


METHODS
This cross-cultural study included students enrolled in the first and second years of their undergraduate medical training. We evaluated depression, anxiety, and stress (DASS 21), empathy, openness to spirituality, and wellness (ESWIM), burnout (Oldenburg), and quality of life (WHOQOL-Bref) and compared them between schools.


RESULTS
A total of 138 Brazilian and 73 US medical students were included. The comparison between all US medical students and all Brazilian medical students revealed that Brazilians reported more depression and stress and US students reported greater wellness, less exhaustion, and greater environmental quality of life. In order to address a possible response bias favoring respondents with better mental health, we also compared all US medical students with the 50% of Brazilian medical students who reported better mental health. In this comparison, we found Brazilian medical students had higher physical quality of life and US students again reported greater environmental quality of life. Cultural, social, infrastructural, and curricular differences were compared between institutions. Some noted differences were that students at the US institution were older and were exposed to smaller class sizes, earlier patient encounters, problem-based learning, and psychological support.


CONCLUSION
We found important differences between Brazilian and US medical students, particularly in mental health and wellness. These findings could be explained by a complex interaction between several factors, highlighting the importance of considering cultural and school-level influences on well-being.
A Deep Learning Approach for Subject Independent Emotion Recognition from Facial Expressions

This paper proposes Deep Learning (DL) models for emotion recognition from facial expressions. We have focused on two “deep” neural models: Convolutional Neural Networks (CNN) and Deep Belief Networks (DBN). For each of these DL neural models, we have chosen several architectures. We have considered both the case of subject independent emotion recognition and also that of subject dependent emotion recognition. One has selected the Support Vector Machine (SVM) as a benchmark algorithm. We have chosen the JAFFE database to evaluate the above proposed models for person independent/dependent facial expression recognition. Using DL approach, we have obtained a subject-independent emotion recognition score of 65.22%, corresponding to an increase of 6% over the best score given by the considered benchmark methods. For person dependent emotion recognition, the DL model leads to the recognition score of 95.71%, representing an increase of 3% over the best of chosen benchmark methods. Key-Words: Facial expression, Deep Learning (DL), Convolutional Neural Networks (CNN), Deep Belief Networks (DBN), subject independent/dependent emotion recognition
Host based intrusion detection using RBF neural networks

A novel approach of host based intrusion detection is suggested in this paper that uses Radial basis Functions Neural Networks as profile containers. The system works by using system calls made by privileged UNIX processes and trains the neural network on its basis. An algorithm is proposed that prioritize the speed and efficiency of the training phase and also limits the false alarm rate. In the detection phase the algorithm provides implementation of window size to detect intrusions that are temporally located. Also a threshold is implemented that is altered on basis of the process behavior. The system is tested with attacks that target different intrusion scenarios. The result shows that the radial Basis Functions Neural Networks provide better detection rate and very low training time as compared to other soft computing methods. The robustness of the training phase is evident by low false alarm rate and high detection capability depicted by the application
An Empirical Study on Measuring the Success of Knowledge Repository Systems

This paper proposes and empirically validates a Knowledge Repository Systems (KRS) Success Model. Based on Mason's information influence theory, we developed a more comprehensive framework for KRS success measurement by combining DeLone and McLean's IS Success Model with Markus's knowledge reusability concept. The data were collected through a survey of 110 KRS users in China and Singapore. The empirical results demonstrate that KRS success should be measured at different stages of knowledge reuse as well as a series of influence on KRS users, and these KRS success dimensions are interrelated.
Inhibition of breast cancer cell migration by activation of cAMP signaling

Almost all deaths from breast cancer arise from metastasis of the transformed cells to other sites in the body. Hence, uncovering a means of inhibiting breast cancer cell migration would provide a significant advance in the treatment of this disease. Stimulation of the cAMP signaling pathway has been shown to inhibit migration and motility of a number of cell types. A very effective way of selectively stimulating cAMP signaling is through inhibition of cyclic nucleotide phosphodiesterases (PDEs). Therefore, we examined full expression profiles of all known PDE genes at the mRNA and protein levels in four human breast cancer cell lines and eight patients’ breast cancer tissues. By these analyses, expression of almost all PDE genes was seen in both cell lines and tissues. In the cell lines, appreciable expression was seen for PDEs 1C, 2A, 3B, 4A, 4B, 4D, 5A, 6B, 6C, 7A, 7B, 8A, 9A, 10A, and 11A. In patients’ tissues, appreciable expression was seen for PDEs 1A, 3B, 4A, 4B, 4C, 4D, 5A, 6B, 6C, 7A, 7B, 8A, 8B, and 9A. PDE8A mRNA in particular is prominently expressed in all cell lines and patients’ tissue samples examined. We show here that stimulation of cAMP signaling with cAMP analogs, forskolin, and PDE inhibitors, including selective inhibitors of PDE3, PDE4, PDE7, and PDE8, inhibit aggressive triple negative MDA-MB-231 breast cancer cell migration. Under the same conditions, these agents had little effect on breast cancer cell proliferation. This study demonstrates that PDE inhibitors inhibit breast cancer cell migration, and thus may be valuable therapeutic targets for inhibition of breast cancer metastasis. Since PDE8A is expressed in all breast cancer samples, and since dipyridamole, which inhibits PDE8, and PF-04957325, a selective PDE8 inhibitor, both inhibit migration, it suggests that PDE8A may be a valuable novel target for treatment of this disease.
Controlled medial branch anesthetic block in the diagnosis of chronic lumbar facet joint pain: the value of a three-month follow-up

OBJECTIVES
To verify the incidence of facetary and low back pain after a controlled medial branch anesthetic block in a three-month follow-up and to verify the correlation between the positive results and the demographic variables.


METHODS
Patients with chronic lumbar pain underwent a sham blockade (with a saline injection) and then a controlled medial branch block. Their symptoms were evaluated before and after the sham injection and after the real controlled medial branch block; the symptoms were reevaluated after one day and one week, as well as after one, two and three months using the visual analog scale. We searched for an association between the positive results and the demographic characteristics of the patients.


RESULTS
A total of 104 controlled medial branch blocks were performed and 54 patients (52%) demonstrated >50% improvements in pain after the blockade. After three months, lumbar pain returned in only 18 individuals, with visual analogue scale scores >4. Therefore, these patients were diagnosed with chronic facet low back pain. The three-months of follow-up after the controlled medial branch block excluded 36 patients (67%) with false positive results. The results of the controlled medial branch block were not correlated to sex, age, pain duration or work disability but were correlated with patient age (p<0.05).


CONCLUSION
Patient diagnosis with a controlled medial branch block proved to be effective but was not associated with any demographic variables. A three-month follow-up is required to avoid a high number of false positives.
Nymble: a High-Performance Learning Name-finder

This paper presents a statistical, learned approach to finding names and other nonrecursive entities in text (as per the MUC-6 definition of the NE task), using a variant of the standard hidden Markov model. We present our justification for the problem and our approach, a detailed discussion of the model itself and finally the successful results of this new approach.
A Real Time Audio Fingerprinting System for Advertisement Tracking and Reporting in FM Radio

In this paper we present a system designed to detect, identify and track commercial segments transmitted by a radio station. The program is entirely written in Visual C++ and uses state of the art audio fingerprinting technologies to achieve a great performance, being able to operate several times faster than real time while keeping a moderate computational load.
Developing mental health mobile apps: Exploring adolescents' perspectives

Mobile applications or 'apps' have significant potential for use in mental health interventions with adolescents. However, there is a lack of research exploring end users' needs from such technologies. The aim of this study was to explore adolescents' needs and concerns in relation to mental health mobile apps. Five focus groups were conducted with young people aged 15-16 years (N = 34, 60% male). Participants were asked about their views in relation to the use of mental health mobile technologies and were asked to give their responses to a mental health app prototype. Participants identified (1) safety, (2) engagement, (3) functionality, (4) social interaction, (5) awareness, (6) accessibility, (7) gender and (8) young people in control as important factors. Understanding end users' needs and concerns in relation to this topic will inform the future development of youth-oriented mental health apps that are acceptable to young people.
GAMIFICATION IN LOGISTICS AND SUPPLY CHAIN EDUCATION : EXTENDING ACTIVE LEARNING

Engagement with users involved in an activity has become increasingly important, particularly in Higher Education. We review the concept of gamification and outline several existing applications. These incorporate game elements into existing systems and tasks in a way that increases user engagement in the process. Current approaches in logistics and supply chain education are discussed in relation to active learning. We develop a framework that combines several gamification elements that can be relatively easily incorporated into existing approaches and learning management systems (LMSs) in ways that aims to increase engagement and extend active learning. This framework and the relationship between the elements provide fertile ground for further research.
Evaluation of Water Quality: Physico - Chemical Characteristics of Ganga River at Kanpur by using Correlation Study

We present an extensive investigation of physico-chemical parameters of water samples of Ganga river at Kanpur. Water samples under investigations were collected from Jalsansthan Benajhawar Kanpur sampling station during pre monsoon (April May), monsoon (July August) and post monsoon (October November) seasons in the year 2008. Correlation coefficients were calculated between different pairs of parameters to identify the highly correlated and interrelated water quality parameters and t-test was applied for checking significance. The observed values of different physico-chemical parameters like pH, temperature, turbidity , total hardness(TH) , Iron , Chloride , total dissolved solids(TDS) , Ca, Mg , SO4 , NO3, F, total alkalinity (TA) , Oxygen consumption (OC), Suspended solids (SS) of samples were compared with standard values recommended by world health organization (WHO). It is found that significant positive correlation holds for TA with Cl, Mg, Ca, TH, TDS, fluoride and OC. A significant negative correlation was found between SS with chloride, Mg, TDS, fluoride and OC. All the physico chemical parameters for pre monsoon, monsoon and post monsoon seasons are within the highest desirable or maximum permissible limit set by WHO except turbidity which was high while NO3 , Cl and F are less than the values prescribed by WHO. [Nature and Science. 2009;1(6):91-94]. (ISSN: 1545-0740).
Linking Cybersecurity Knowledge : Cybersecurity Information Discovery Mechanism

To cope with increasing amount of cyber threats, organizations need to share cybersecurity information beyond the borders of organizations, countries, and even languages. Assorted organizations built repositories that store and provide XML-based cybersecurity information on the Internet. Among them are NVD [1], OSVDB [2], and JVN [3], and more cybersecurity information from various organizations from various countries will be available in the Internet. However, users are unaware of all of them. To advance information sharing, users need to be aware of them and be capable of identifying and locating cybersecurity information across such repositories by the parties who need that, and then obtaining the information over networks. This paper proposes a discovery mechanism, which identifies and locates sources and types of cybersecurity information and exchanges the information over networks. The mechanism uses the ontology of cybersecurity information [4] to incorporate assorted format of such information so that it can maintain future extensibility. It generates RDF-based metadata from XML-based cybersecurity information through the use of XSLT. This paper also introduces an implementation of the proposed mechanism and discusses extensibility and usability of the proposed mechanism.
Maintenance treatment for old-age depression preserves health-related quality of life: a randomized, controlled trial of paroxetine and interpersonal psychotherapy.

OBJECTIVES
To determine whether maintenance antidepressant pharmacotherapy and interpersonal psychotherapy sustain gains in health-related quality of life (HR-QOL) achieved during short-term treatment in older patients with depression.


DESIGN
After open combined treatment with paroxetine and interpersonal psychotherapy, responders were randomly assigned to a two (paroxetine vs placebo) by two (monthly interpersonal psychotherapy vs clinical management) double-blind, placebo-controlled maintenance trial. HR-QOL outcomes were assessed over 1 year.


SETTING
University-based clinic.


PATIENTS
Of the referred sample of 363 persons aged 70 and older with major depression, 210 gave consent, and 195 started acute treatment; 116 met criteria for recovery, entered maintenance treatment, and were included in this analysis.


INTERVENTIONS
Paroxetine; monthly manual-based interpersonal psychotherapy.


MEASUREMENTS
Overall HR-QOL as measured using the Quality of Well-Being Scale (QWB) and six specific HR-QOL domains derived from the Medical Outcomes Study 36-item Short-Form Health Survey (SF-36) subscales.


RESULTS
All domains of HR-QOL except physical functioning improved with successful acute and continuation treatment. After controlling for any effects of psychotherapy, pharmacotherapy was superior to placebo in preserving overall well-being (P=.04, effect size (r)=0.23), social functioning (P=.02, r=0.27), and role limitations due to emotional problems (P=.007, r=0.30). Interpersonal psychotherapy (controlling for the effects of pharmacotherapy) did not preserve HR-QOL better than supportive clinical management.


CONCLUSION
Maintenance antidepressant pharmacotherapy is superior to placebo in preserving improvements in overall well-being achieved with treatment response in late-life depression. No such benefit was seen with interpersonal psychotherapy.
A Systematic Review of Research on Open Source Software in Commercial Software Product Development

Background: The popularity of the open source software development in the last decade, has brought about an increased interest from the industry on how to use open source components, participate in the open source community, build business models around this type of software development, and learn more about open source development methodologies. Aim: The aim of this study is to review research carried out on usage of open source components and development methodologies by the industry, as well as companies’ participation in the open source community. Method: Systematic review through searches in library databases and manual identification of articles from the open source conference. Results: 19 articles were identified. Conclusions: The articles could be divided into four categories: open source as part of component based software engineering, business models with open source in commercial organization, company participation in open source development communities, and usage of open source processes within a company.