Miracle-dz/UniFAR-FTUs huggingface dataset:
What is the minimal nutrition education dosage to achieve behavior change for SNAP‐Ed participants?

SNAP‐Ed increases the ability of low‐income families to make healthy food choices with the long‐term objective of preventing diet‐related diseases through nutrition education. As a national program, SNAP‐Ed needs to make the best use of its available resources. The dosage of nutrition education lessons needed to achieve measurable behavior change is unknown. This study aims to define the minimum nutrition education dosage needed to achieve measurable behavior change in SNAP‐Ed participants. Self‐reported (n=28) degrees of behavior change on four indicators on fruits and vegetables consumption were measured using the Ohio SNAP‐Ed Fruit and Vegetable Retrospective Questionnaire at four time points (baseline, after 1 lesson, after 3 lessons, and after 6 lessons). Univariate repeated measures ANOVA showed a positive and significant dosage effect from 1 lesson to 6 lessons on “eating fruits and vegetables of different colors each day” (p ≤ 0.011); “eating more than one kind of fruit each day” (p ≤ 0.003); and “eating fruits and vegetables as snacks” (p ≤ 0.008). The effect of dosage for “eating more than one kind of vegetable each day” approached significance (p ≤ 0.077). These findings indicate that more lessons on fruits and vegetables consumption leads to greater behavior change in up to six lessons. At this point we are unable to identify a ceiling beyond 6 lessons.
Vascular Network Analysis with Manual and Automatic Segmentation Using Fuzzy Mathematical Morphology

The inhibition of new vessel creation, or anti-angiogenesis, has therapeutic interest. In this contribution, we introduce an automatic method to estimate objective indicators of new vessel creation. We use images of the chorioallantoic membrane of chicken embryos, some of which have been injected with a varying degree of methyl jasmonate, which has anti-angiogenic effects. We use fuzzy mathematical morphology to compute an automatic vessel segmentation, which along with the manual ground truth is used to study which features indicating the creation of new vessels can be replicated. Employing hypothesis tests and a PCA analysis, we conclude that our limited database provides positive but moderate results in terms of the statistical significance of the difference of such samples.
Keyframe Based Human Activity Recognition Using Random Forests

Human activities are characterized as being complex, not only for their temporal and spacial patterns, but also because of the fact humans are physically di erent. When the same activity is performed by di erent persons, or even by the same one, they can execute the same activity with distinct motion properties. In this sense, there is the need to incorporate machine learning approaches able to integrate all this variability. However, even with the increasingly attention this eld of research is getting, current learning approaches, although accurate, are very slow to train and classify. These limitations turn infeasible their use in real-time applications, where a robot must rapidly and correctly identify a performed activity, in order to respond accordingly. A human activity recognition framework, featuring fast training and requiring few training examples, is therefore proposed, consisting of two main components: a features extraction approach component (i.e. extraction of relevant information describing a certain activity) and a machine learning component, based on the random forest classi er. An initial concept of segmenting each activity into a sequence of xed-size actions is employed (i.e. no frame-by-frame classi cation), extracting just maximum and minimum values of each extracted skeleton-based feature. After some experimental validation, a second approach was developed and tested, considering the division of each activity into variable-size windows, based on key poses. Each action window is delimited by two consecutive and automatically identi ed key poses, where static (i.e. geometrical) and maximum and minimum dynamic (i.e. temporal) features are extracted. First, these approaches were tested using the Cornell Activity Dataset and the random forest classi er provided by Weka Software, obtaining relevant overall average results. Then a custom random forest classi er was developed from scratch, using a di erential evolution algorithm, as part of its core. The developed random forest was tested and its results compared to the ones obtained with Weka's random forest, suggesting a slight increase in terms of the considered performance indicators. A custom dataset was built, using data from a RGB-D sensor, and both random forest classi ers were
Perancangan Sistem Informasi Pemetaan Pariwisata Garut Berbasis Geografic Information System dan Android

Perancangan Sistem Informasi Pemetaan Pariwisata Garut Berbasis Geografic Information Sistem dan Android merupakan salah satu pengembangan sistem yang terkomputerisasi dalam bidang teknologi informasi dengan latar belakang sulitnya untuk mendapatkan informasi akan objek wisata dikarenakan untuk mendapatkan informasi dari objek wisata tersebut harus dari orang yang sudah pernah berkunjung ke tempat wisata tersebut. Adapun tujuan dari aplikasi ini adalah untuk merancang sebuah sistem informasi pemetaan pariwisata garut berbasis geografic information system dan mobile android. Metode perancangan sistem yang digunakan menggunakan metodologi RAD (Rapid Application Development) dengan Tahapan yang dilakukan dalam RAD yaitu Scope Definition, Analysis, Design, Construction & Testing. Dari hasil yang dicapai pada penelitian ini berupa aplikasi pemetaan pariwisata Garut berbasis geografic information system dan android yang mampu menampilkan data pariwisata dengan dibagi kedalam 4 kategori yaitu wisata alam, wisata budaya, wisata minat khusus, dan wisata rekreasi. Dari data wisata tersebut dapat disajikan dengan peta lokasi wisata, petunjuk jalan dari pengguna pertama kali mengakses aplikasi, foto-foto dari objek wisata tersebut beserta infomasi mengenai lokasi wisata tersebut.
Prosody Prediction from Syntactic, Lexical, and Word Embedding Features

Accurate prosody prediction from text leads to more natural-sounding TTS. In this work, we employ a new set of features to predict ToBI pitch accent and phrase boundaries from text. We investigate a wide variety of text-based features, including many new syntactic features, several types of word embeddings, co-reference features, LIWC features, and speciﬁcity information. We focus our work on the Boston Radio News Corpus, a ToBI-labeled corpus of relatively clean news broad-casts, but also test our classiﬁers on Audix, a smaller corpus of read news, and on the Columbia Games Corpus, a corpus of conversational speech, in order to test the applicability of our model in cross-corpus settings. Our results show strong performance on both tasks, as well as some promising results for cross-corpus applications of our models.
Revolution in Egypt: Political Movements and Mobilisation of Resources

This article discusses the application of the resource mobilisation theory (RMT) to clarify the activities of certain key socio-political movements in Egypt. It contends that the political movements in Egypt have utilised social networking sites (SNSs) as a tool for mobilising people and co-ordinating anti-regime activities. It deals with certain political groups prior to and throughout the revolution in Egypt, which played significant roles in recent political changes taking place in the country. This work confirmed that SNSs have become a crucial resource for political groups to bringing about collective and co-ordinated actions. Thus, the article elucidates the importance of RMT in the context of socio-political movements in Egypt and their subsequent influence by looking at the utilisation of social media throughout political uprisings in the country. As per the RMT, the SNSs could be used as a resource for promoting and succeeding anti-government political groups, which subsequently ended the regime.
Dynamic Joint Reconstruction of Walls and Targets in Through-the-Wall Radar Imaging

Multipath exploitation with compressive sensing (CS) has been successfully applied in through-the-wall radar imaging (TWRI) given prior knowledge of the room geometry. However, in most practical applications and critical missions, the geometry of the room is not known. In this paper dynamic wall pursuit algorithm is proposed to simultaneously recover the room geometry and image the scene behind the wall. We demonstrate that moving targets increase the wall reconstruction accuracy. The algorithm exploits the fact that wrong wall positions populate the reconstructed image with false targets. It makes use of the moving targets in the scene to increase the certainty of the detected wall positions. Simulated results show the effectiveness of this method even at low SNR values.
Deep Learning for Joint Acoustic Echo and Noise Cancellation with Nonlinear Distortions

We formulate acoustic echo and noise cancellation jointly as deep learning based speech separation, where near-end speech is separated from a single microphone recording and sent to the far end. We propose a causal system to address this problem, which incorporates a convolutional recurrent network (CRN) and a recurrent network with long short-term memory (LSTM). The system is trained to estimate the real and imaginary spectrograms of near-end speech and detect the activity of near-end speech from the microphone signal and far-end signal. Subsequently, the estimated real and imaginary spectrograms are used to separate the near-end signal, hence removing echo and noise. The trained near-end speech detector is employed to further suppress residual echo and noise. Evaluation results show that the proposed method effectively removes acoustic echo and background noise in the presence of nonlinear distortions for both simulated and measured room impulse responses (RIRs). Additionally, the proposed method generalizes well to untrained noises, RIRs and speakers.
Artificially Intelligent Law

This paper explores a series of thought experiments that postulate the ex-istence of “artificially intelligent law. ” An artificially-intelligent legal system is de-fined as one with three functional capacities: 1. The system has the capacity to gen-erate legal norms. 2. The system has the capacity to apply the legal norms that it generates. 3. The system has the capacity to use deep learning to modify the legal norms that it generates. The paper then considers the question whether such a sys-tem would be desirable as a matter of legitimacy and justice. The core idea of the paper is that the key to the evaluation of artificially intelligent law is to focus on the functional capacities of the system in comparison to comparable human systems, such as regulatory agencies.
Classical and Emerging Risk Factors for Cardiovascular Disease

Medicine, invited experts summarize the current status of risk factors for vascular disease. These include descriptions of the risk factors and their measurement; their reported associations with CHD, stroke, and POAD in cross-sectional, case-control, and prospective observational studies (with pooled analyses and meta-analyses where available); and where possible, quantitative appraisal of the evidence from randomized interventional studies of the potential for disease prevention. We have included both “classical,” established risk factors and “emerging” risk factors whose causal role has yet to be defined. The latter group include markers of infections, inflammation, and thrombosis, which are plausible mechanisms for the rupture of atherosclerotic plaques and the consequent thrombotic vascular occlusion, which initiates infarction of the heart, brain, or limb. We have not included two areas that have recently been comprehensively reviewed in Seminars in Vascular Medicine: Diabetes (Volume 2, February and May 2002) and sex hormones (Volume 1, 2002). In this issue, a summary of the current status of common genetic polymorphisms is followed by reviews of the “behavioral” environmental risk factors: smoking, alcohol consumption, exercise, and psychosocial factors. Blood lipid fractions, which are established or potential mechanisms in atherothrombosis (cholesterol, HDL cholesterol, triglycerides, and lipoprotein [a]) are then considered. The second issue will contain reviews of other mechanisms for atherothrombosis: blood pressure and markers of infection, inflammation, and thrombosis. We thank all the authors for their contributions, and hope that readers will find them as informative and useful as we have.
The Removal of Silicate(IV) by Adsorption onto Hydrocalumite from the Sodium Hydroxide Leaching Solution of Black Dross

Alkaline leaching of mechanically activated black dross resulted in an aluminate(III) solution with a small amount of silicate(IV). To obtain pure aluminate(III) solution, the removal of silicate(IV) from the alkaline leaching solution was investigated by adsorption with hydrocalumite (Ca2Al(OH)6Cl·2H2O). The hydrocalumite was synthesized by the coprecipitation method. The characterization of the synthesized hydrocalumite was analyzed via X-ray diffraction (XRD), scanning electron microscopy (SEM) images and Fourier-transform infrared spectroscopy (FTIR). In our experimental conditions, silicate(IV) was selectively adsorbed onto hydrocalumite over aluminate(III). The reaction time greatly affected the removal percentage of aluminate(III) owing to mass action effect. When the reaction time was longer than 2 h, no aluminate(III) was adsorbed onto hydrocalumite and thus it was possible to selectively remove silicate(IV). When the dosage of hydrocalumite was in excess, the removal percentage of silicate(IV) was rather reduced. Complete removal of silicate(IV) from the solution was accomplished in the reaction temperature between 50 and 70 °C. By selective adsorption of silicate(IV) from the solution at the optimum condition (30 g/L hydrocalumite, 50 °C, 400 rpm, and 2 h), an aluminate(III) solution with purity higher than 99.9% was obtained. The adsorption of silicate(IV) onto hydrocalumite followed the Freundlich isotherm.
Listening with Great Expectations: An Investigation of Word Form Anticipations in Naturalistic Speech

The event-related potential (ERP) component named phonological mismatch negativity (PMN) arises when listeners hear an unexpected word form in a spoken sentence [1]. The PMN is thought to reflect the mismatch between expected and perceived auditory speech input. In this paper, we use the PMN to test a central premise in the predictive coding framework [2], namely that the mismatch between prior expectations and sensory input is an important mechanism of perception. We test this with natural speech materials containing approximately 50,000 word tokens. The corresponding EEG-signal was recorded while participants (n = 48) listened to these materials. Following [3], we quantify the mismatch with two word probability distributions (WPD): a WPD based on preceding context, and a WPD that is additionally updated based on the incoming audio of the current word. We use the between-WPD cross entropy for each word in the utterances and show that a higher cross entropy correlates with a more negative PMN. Our results show that listeners anticipate auditory input while processing each word in naturalistic speech. Moreover, complementing previous research, we show that predictive language processing occurs across the whole probability spectrum.
Alcohol and hazardous drinking in Russia : a mixed design study

This thesis investigated drinking patterns in the Russian city of Novosibirsk, with a specific focus on hazardous drinking. It explored the relationship between hazardous drinking and social-economic characteristics, depressive symptoms and self-reported health. The study also provided an in-depth description of drinking patterns, consumption of ‘surrogate’ alcohol, and perceptions of the Russian drinking culture and the state’s alcohol policies. The research used a combination of quantitative and qualitative methods. First, it assessed alcohol consumption and drinking patterns using data from the HAPIEE (Health, Alcohol and Psychosocial factors In Eastern Europe) cohort. Second, a series of 44 semi-structured interviews were conducted with men and women sampled from the HAPIEE cohort. Third, 40 semi-structured interviews were conducted among clients of an alcohol treatment facility. These interviews were focused on hazardous drinking. The main findings were as follows. First, hazardous drinking was common among men, but rare among women (30% of men and 1% of women reported binge drinking, 19% of men and 1% of women reported problem drinking, and 9% of men and less than 1% of women reported more than two negative consequences of drinking). Second, hazardous drinking was associated with lower education (e.g. men with secondary education were 1.9 times more likely to binge drink than men with university education), unemployment, poor health (men and women rating their health as good were more likely to binge than people with poor health), and with certain occupations (e.g. drivers or construction workers were likely to report binge drinking). Third, high accessibility of alcohol and a need to relieve withdrawal symptoms were common reasons for surrogate consumption given in interviews by participants from alcohol treatment facility. Finally, the Russian drinking culture was perceived as characterised by heavy drinking and strongly influenced by the interplay of individual and structural factors.
Inhibition of PDGF receptor signaling in tumor stroma : effects on interstitial hypertension, drug uptake and therapeutic response.

Lowering of tumor interstitial hypertension, which acts as a barrier for tumor transvascular transport, has been proposed as a general strategy to enhance tumor uptake and therapeutic effects of anticancer drugs. The tyrosine kinase platelet-derived growth factor (PDGF) beta-receptor is one mediator of tumor hypertension. The effects of PDGF antagonists on chemotherapy response were investigated in two tumor models that display PDGF receptor expression restricted to the tumor stroma, and in which PDGF antagonists relieve tumor hypertension. Inhibitory PDGF aptamers and the PDGF receptor tyrosine kinase inhibitor STI571 enhanced the antitumor effect of Taxol on s.c. KAT-4 tumors in SCID mice. Treatment with only PDGF antagonists had no effect on tumor growth. Taxol uptake in tumors was increased by treatment with PDGF antagonists. Cotreatment with PDGF antagonists and Taxol was not associated with antiangiogenic effects, and PDGF antagonists did not enhance the Taxol effect on in vitro growth of KAT-4 cells. STI571 also increased the antitumor effects of 5-fluorouracil on s.c. PROb tumors in syngeneic BDIX rats, without increasing the effect of 5-fluorouracil on cultured PROb cells. Expression of PDGF receptors in tumor stroma, as well as tumor hypertension, occurs in most common solid tumors. Therefore, our results have implications for treatment regimens for large patient groups and merit clinical testing. In conclusion, our study identifies inhibition of PDGF signaling in tumor stroma as a novel, possibly general strategy for enhancement of the therapeutic effects chemotherapy.
Wybrane charakterystyki oceny dzialania europejskich systemow ochrony zdrowia – perspektywa pacjenta. (Selected characteristics of the performance evaluation of European health care systems – the perspective of patient.)

An aging population, progress in medical technology and rising public expectations of provided health services is just one of many challenges facing today’s health care systems. One of the key factors of research in the analyzed national health systems is the ability to effectively achieve its objectives. The Authors of this thesis, tempted to analyze the efficiency of system’s operations by discussing the assessments made by patients and consumers in European countries obtained using a similar methodology in the years 2007, 2009, 2012. The study was conducted by the research institute Health Consumer Powerhouse (HCP). Analysis covered the results of subjective evaluation of selected areas of health care system’s activity. Furthermore we characterized the expenditures and spending on health in these countries, which in EHCI were rewarded with the highest score. In conclusion, the authors have conducted the discussion which classic health care models seem to have a greater social acceptance and acquiescence for the action.
The Role of Public Participation in Environmental Governance: Empirical Evidence from China

As an essential stakeholder of environmental resources, the public has become the third force which assists in promoting environmental governance, together with local governments and polluting enterprises. In this paper, we construct a mediation model and a 2SLS (Two Stage Least Square) model to illustrate the role of public participation based on inter-provincial panel data of China from 2011 to 2015. The results indicate that the advantages of handling informational asymmetry and enhancing social supervision are the two logical starting points of involving public participation in environmental governance. As the public has no executive power, they can participate in environmental governance in an indirect way by lobbying local governments’ environmental enforcement of polluting enterprises. In addition, their deterrent of polluting enterprises can also generate effects similar to local governments’ environmental enforcement, and such a deterrent will help promote environmental governance directly. At the present time in China, the effects of public participation in environmental governance are mainly reflected in the form of back-end governance, while the effects of front-end governance are not remarkable enough. This research is of great significance in perfecting China’s environmental governance system by means of arousing and expanding the public’s rights to participate in environmental governance.
Factors associated with complications of vascular access site in hemodialysis patients in Isfahan Aliasghar hospital

Background: Vascular access complications are a major cause of excessive morbidity and mortality in the dialysis population. Moreover, there is not sufficient research regarding the factors correlated with vascular access complications among hemodialysis patients. This study aimed to evaluate the vascular access complications and their related factors such as nursing techniques and self-care in hemodialysis patients. Materials and Methods: A cross-sectional study was performed on 110 patients undergoing hemodialysis in Isfahan Aliasghar hospital during 9 months from July 2010 to March 2011. The data collection tools were a demographic questionnaire and three checklists designed to assess the complications of vascular access and care techniques. Data were collected by observations and interviews with the patients. Fisher’s exact test, chi‑square test, Pearson correlation coefficient, and descriptive statistics were used to analyze the data through SPSS 16. Results: Among 110 subjects, there were 63 male and 47 female subjects. Subjects’ mean age was 55.88 (15.51) years. There were 72 patients undergoing hemodialysis through arteriovenous fistula and 38 through permanent intra‑jugular catheters. Insufficient blood flow in the catheter was the most common complication in patients with jugular catheters. Also, aneurysm was the most prevalent complication in patients with arteriovenous fistula. Low self‑care of patients and needling into the aneurysm were correlated with aneurysm size. Presence of underlying diseases was related to ischemia. Conclusions: Nursing techniques and self‑care of patients were correlated with the occurrence of complications. Therefore, it draws the attention of the nurses toward continuing professional education and patients’ education, which can increase the longevity of vascular access.