Miracle-dz/UniFAR-FTUs huggingface dataset:
Using Sentiment Data from the Global Database for Events, Language and Tone (GDELT) to Predict Short-Term Stock Price Developments

This study is set to investigate whether media sentiment, retrieved from the Global Database of Events, Language and Tone, can be a predictor of stock price. A business process model for the extraction and utilization of sentiment data from GDELT is presented and used for measuring the cross-correlation between average media sentiment and closing stock price of Facebook, Apple, Amazon, Alphabet and Tesla. A total of more than 5 million news article entries from GDELT were analyzed, 58.655 of which are relevant to this research. Alphabet is the only company with a strong positive cross-correlation of average daily media sentiment with adjusted closing stock price on the same day, while Facebook and Tesla exhibit weak negative correlations.
Photodynamic tumor therapy : quantitative data on 2nd and 3rd generation photosensitizers

The introductory section of this text provides a framework for standardizing results in biophysical terms. It is comprised of biophysical and biomedical definitions describing photosensitization and phototoxicity on the molecular and cellular level. The available data regarding naturally occurring and chemically synthesized compounds is grouped together into synoptic tables and graphs in the second section. The inclusion of preparation methods and purity control, as well as improved application schedules to cell cultures and experimental animals, makes this section extremely useful as a biomedical research laboratory manual. The concluding section is devoted to the potential future applications of these photosensitizers to photodynamic therapy in patients. The main topics include the necessary prerequisites for improved uptake of the sensitizers by tumor cells and inflamed tissue; tumor targeting by combined application of carrier systems and tumor specific monoclonal antibodies;
Profiling Speech Motor Impairments in Persons with Amyotrophic Lateral Sclerosis: An Acoustic-Based Approach

The goal of this study was to profile the speech motor impairments that characterize dysarthria secondary to amyotrophic lateral sclerosis (ALS). This information is important for identifying optimal treatment strategies and guiding speech impairment subtype discovery, which may facilitate ongoing efforts to improve automatic speech recognition (ASR) of dysarthric speech. Speech motor impairments were profiled by introducing a novel framework that assesses four key components of motor control: coordination, consistency, speed, and precision. An individual acoustic feature was selected to represent each component. Specifically, coordination was indexed by the proportion of voice onset time (VOT) to syllable duration, consistency by the coefficient of variation of VOT between repetitions of /pataka/ within each distinct consonant, speed by the slope of the second formant (F2), and precision by the standard deviation of F2 slope between distinct consonants within each repetition of /pataka/. Acoustic measures were extracted from audio recordings of each participant (18 controls and 14 participants with ALS) during a sequential motion rate (SMR) task. Results revealed that the primary underlying speech motor impairments that characterize ALS are in coordination, speed, and precision. Further research is needed to validate the existence of speechimpairment-based subtypes across the continuum of speech motor disorders.
Signal Fuse Learning Method With Dual Bands WiFi Signal Measurements in Indoor Positioning

Today, indoor localization technology based on WiFi signals has become more and more popular and applicable. It not only facilitates people’s lives but also creates enormous economic value. However, during the propagation of the WiFi signal, it is easily interfered by obstacles, and the signal fluctuation is significant, resulting in low accuracy of positioning. To overcome these problems, we reduce the influence of environmental factors firstly. Then the positioning accuracy is improved by using the SVM model to distinguish the NLOS or LOS environment and employing the capsule networks to derive the users’ positions with the WiFi 2.4G and 5G signals. As we all know, the WiFi 2.4G signal has excellent penetrability and is less affected by obstacles, while the WiFi 5G signal has excellent stability and small fluctuations. Therefore, we use the advantages of these two kinds of signals to derive the optimal suggestion by the capsule neural network, which is the learning system with minimum data sets needed. The experimental results show that the positioning effect of the two signals simultaneously is better than the positioning effect of a single signal. We also compare with the traditional indoor positioning methods and use the simulation data to carry out the robustness test, and the positioning accuracy reached 0.99 m in the field environment finally.
Evaluation of anti-inflammatory activity of ethanolic extract of Cananga odorata Lam in experimental animals -

Background: The current study evaluates the anti-inflammatory activity of ethanolic extract of Cananga odorata Lam (EECO) in experimental animals. Methods: Acute toxicity test was done following OECD guidelines. Carrageenan induced paw edema method in Wistar Albino rats were used in this study. Aspirin in the dose of 300 mg/kg was used as the standard drug and three doses of EECO (100 mg/kg, 200 mg/kg and 400 mg/kg b.w. p.o) were used as the test drug. The results were measured at 1 st hr, 3 rd hr and 5 th hr after carrageenan injection. Results: EECO in the doses of 100 mg/kg, 200 mg/kg and 400 mg/kg showed highly significant anti-inflammatory activity (p<0.001) (p<0.001) (p<0.001) at 3 rd hr and (p<0.001) (p<0.001) (p<0.001) 5 th hr, respectively. In doses of 100 mg/kg, 200 mg/kg, and 400 mg/kg of EECO showed the percentage of inhibition of 62.9% which is more than the standard drug aspirin, which showed 60.14% inhibition. Conclusion: EECO has significant anti-inflammatory activity.
The power to define resilience in social–hydrological systems: Toward a power‐sensitive resilience framework

Since the early work on defining and analyzing resilience in domains such as engineering, ecology and psychology, the concept has gained significant traction in many fields of research and practice. It has also become a very powerful justification for various policy goals in the water sector, evident in terms like flood resilience, river resilience, and water resilience. At the same time, a substantial body of literature has developed that questions the resilience concept's systems ontology, natural science roots and alleged conservatism, and criticizes resilience thinking for not addressing power issues. In this study, we review these critiques with the aim to develop a framework for power‐sensitive resilience analysis. We build on the three faces of power to conceptualize the power to define resilience. We structure our discussion of the relevant literature into five questions that need to be reflected upon when applying the resilience concept to social–hydrological systems. These questions address: (a) resilience of what, (b) resilience at what scale, (c) resilience to what, (d) resilience for what purpose, and (e) resilience for whom; and the implications of the political choices involved in defining these parameters for resilience building or analysis. Explicitly considering these questions enables making political choices explicit in order to support negotiation or contestation on how resilience is defined and used.
Target Speaker Recovery and Recognition Network with Average x-Vector and Global Training

It is very challenging to do multi-talker automatic speech recognition (ASR). Some speaker-aware selective methods have been proposed to recover the speech of the target speaker, relying on the auxiliary speaker information provided by an anchor (a clean audio sample of the target speaker). But the performance is unstable depending on the quality of the provided anchors. To address this limitation, we propose to take advantage of the average speaker embeddings to build the target speaker recovery network (TRnet). The TRnet takes the mixed speech and the stable average speaker embeddings to produce the TF masks for the target speech. During training of the TRnet, we summarize the speaker embeddings on the whole training dataset for each speaker, instead of extracting on a randomly picked anchor. On the testing stage, one or very few anchors are enough to get decent recovery results. The results of the TRnet trained with average speaker embeddings show 13% and 12.5% relative improvements on WER and SDR, compared with the short-anchor trained model. Moreover, to mitigate the mismatch between the TRnet and the acoustic model (AM), we adopted two strategies: fine-tuning the AM and training an global TRnet. Both of them bring considerable reductions on WER. The results show that the global trained framework gets superior performance.
Fisheries management in Malawi: a patchwork of traditional, modern, and post-modern regimes unfolds

Malawi is a land-locked country in southern Africa that is renowned for its warm hospitality, scenic beauty, and aquatic biodiversity (estimated at 500–1000 endemic species of fish). However, this nation has recently also been burdened by a series of droughts, the HIV/AIDS epidemic, which is currently estimated to infect 940,000 Malawians, (UNAIDS 2006) and a poor economy, that combine to give it one of the lowest Human Development Index rankings in Southern Africa (UNDP 2005). Given these livelihood constraints, the aquatic biodiversity of Lakes Malawi, Malombe, Chiuta, Chilwa, and the Shire River (see Figure 1) is all the more important, as it provides primary or secondary livelihoods for an estimated 350,000 people, (FAO 2005) and contributes to the incomes of an estimated 1,000,000 people (Malawi 1999). Finally, fish is the cheapest source of animal protein available to Malawians, and due to population growth, the annual per capita amount of fish available has decreased from 12.9 kg in 1976 to just 3.6 kg in 2001 (FAO 2005). Over the course of the later 1900s, the International Governance of Fisheries Ecosystems: 53–98 © 2008 American Fisheries Society
Ministère de la Santé, de la Jeunesse et des Sports

Le ministre du travail, des relations sociales et de la solidarité et la ministre de la santé, de la jeunesse et des sports, Vu le code du travail, et notamment son article L. 920-4 ; Vu le code de la santé publique, et notamment ses articles R. 4383-2 à R. 4383-7 ; Vu le décret n° 2002-615 du 26 avril 2002, pris pour application de l'article L. 900-1 du code du travail et des articles L. 335-5 et L. 335-6 du code de l'éducation, relatif à la validation des acquis de l'expérience pour la délivrance d'une certification professionnelle ; Vu l'arrêté du 26 mars 2002 modifié relatif au diplôme d'Etat d'auxiliaire de vie sociale ; Vu l'arrêté du 12 février 2004 relatif au diplôme d'Etat de médiateur familial ; Vu l'arrêté du 8 juin 2004 modifié relatif au certificat d'aptitude aux fonctions d'encadrement et de responsable d'unité d'intervention sociale ; Vu l'arrêté du 29 juin 2004 relatif au diplôme d'Etat d'assistant de service social ; Vu l'arrêté du 25 janvier 2005 modifié relatif aux modalités d'organisation de la validation des acquis de l'expérience pour l'obtention du diplôme professionnel d'aide-soignant ; Vu l'arrêté du 16 novembre 2005 relatif au diplôme d'Etat d'éducateur de jeunes enfants ; Vu l'arrêté du 16 janvier 2006 relatif à aux modalités d'organisation de la validation des acquis de l'expérience pour l'obtention du diplôme d'auxiliaire de puériculture ; Vu l'arrêté du 14 mars 2006 relatif au diplôme d'Etat d'assistant familial ; Vu l'arrêté du 11 avril 2006 relatif au diplôme d'Etat d'aide médico-psychologique ; Vu l'arrêté du 25 avril 2006 relatif au diplôme d'Etat de technicien de l'intervention sociale et familiale ; Vu l'arrêté du 31 juillet 2006 modifié relatif aux modalités d'organisation de la validation des acquis de l'expérience pour l'obtention du diplôme de préparateur en pharmacie hospitalière ; Vu l'arrêté du 2 août 2006 relatif à la formation conduisant au diplôme de préparateur en pharmacie hospitalière ; Vu l'arrêté du 19 décembre 2006 fixant le modèle du formulaire « Demande de validation des acquis de l'expérience pour l'obtention d'un diplôme ou certificat délivré au nom des ministres chargés de la santé ou de l'action sociale », Arrêtent :
Degradation and biodegradability enhancement of chloramphenicol and azithromycin in aqueous solution using heterogeneous catalytic ozonation in the presence of MGO nanocrystalin comparison with single ozonation

The catalytized ozonation of antibiotic solution in the presence of Mg Onanocrystal as a catalyst was studied in a pilot scale batch reactor. The effects of various variables such as pH (3â��13), reaction time, MgO dosage (0â��10 g/L), and initial antibiotic concentration (0â��50 mg/L) on CAP and AZM removal were investigated, and the results were compared to non-catalyzed ozonation. The optimized pH and catalyst dosage were found to be 8.5 and 6 g/L, respectively. The complete removal of CAP was found in COP at this optimum condition for an antibiotic concentration of 50 mg/L at a reaction time as little as 6 min, while the time needed to achieve the similar removal at conventional ozonation was 30 min. Moreover, the catalytized ozonation can significantly enhance the BOD5 /COD ratio from below 0.1 in untreated solution to 0.41 to 0.68 for treated solutions; therefore, antibiotic was transformed to biodegradable substances. Thus, the COP with MgOnanocrystalscanbe taken into account as an feasible and effective technique for pre-treating the antibiotic-laden solutions, allowing the final-purified of the effluent in a biological treatment plant. Â© 2016, International Journal of Pharmacy and Technology. All rights reserved.
Compressive Sensing based Channel Estimation in OFDM Systems

: Compressive Sensing (CS) is a new sensing modality, which compresses the signal being acquired at the time of sensing. Signals can have sparse or compressible representation either in original domain or in some transform domain. Relying on the sparsity of the signals, CS allows us to sample the signal at a rate much below the Nyquist sampling rate. Also, the varied reconstruction algorithms of CS can faithfully reconstruct the original signal back from fewer compressive measurements. This fact has stimulated research interest toward the use of CS in several fields, such as magnetic resonance imaging, high-speed video acquisition, and ultrawideband communication. This paper reviews the basic theoretical concepts underlying CS. To bridge the gap between theory and practicality of CS, different CS acquisition strategies and reconstruction approaches are elaborated systematically in this paper. The major application areas where CS is currently being used are reviewed here. This paper also Highlights some of the challenges and research directions in this field.
Objective evaluation of similarity scores derived by Evofinder® system for marks on bullets fired from Chinese Norinco QSZ-92 pistols

Abstract In recent years, many studies have been conducted in the field of firearm identification with the objective of providing an objective method of evaluating the comparison of cartridge cases. However, less attention has been paid to the objective evaluation of bullet comparisons. In this study, 1 000 registered Chinese Norinco QSZ-92 pistols were used, and a database of 2 996 bullets was constructed. Both the receiver operating characteristic (ROC) curve and the score-based likelihood ratio method were used to objectively evaluate the similarity scores derived by the Evofinder® system. The results indicate that this system has excellent ability to discriminate between the selected pistols. This paper proposes an objective evaluation method, which serves as a response to the ongoing debates regarding the foundation of the discipline.
FPGA Library Based Design of a Hardware Model for Convolutional Neural Network with Automated Weight Compression using K-Means Clustering

In this paper, a design of a synthesizable hardware model for a Convolutional Neural Network (CNN) is presented. The hardware model is capable of self-training i.e. without the use of any external processors. It is trained to recognize four numerical digit images. Another hardware model is also designed for the K-means clustering algorithm. This second hardware model is used to for compressing the weights of the CNN through quantization. Weight compression is carried out through weight sharing. With weight sharing, the system is able to save component usage. The two hardware models designed are then subsequently integrated to automate the compression of the CNN weights after the CNN completes its training. The entire design is based on fixed point arithmetic operation using VHDL as design entry tool and XILINX Virtex 5 FPGA as the target library for synthesis. After completing the design, it is evaluated in terms of hardware consumption with respect to rate of compression. When evaluating the recognition performance ability of the hardware model, digit images experimentation results have shown that the weight compression can reach as high as 60% without any negative effect on the performance of the CNN. Based on data gathered, the compression with the least hardware consumption occurs at 80 %. For the various digits trained, the CNN outputs after the training, range from 89% to 97%.
The Estimation and Compensation of the Loop-Parameter-Drifting in the Digital Close-Loop Quartz Flexible Accelerometers

There have been increasing demands for the long-term performance retention of the Quartz Flexible Accelerometers (QFA), extensively employed in the Inertial Navigation System (INS). Considering the convenience of conducting the parameter identification and control algorithm, the Digital Close-Loop QFA (Digital-QFA) is established to improve the long-term performance. Based on the model of the entire close-loop system, the interfering factors relating to time are analyzed in detail, both in the forward channel and the feedback channel. Two schedules are proposed to estimate the gain variation, utilizing the modulating signal and the feedback signal separately. According to the reference gain settings in ideal conditions, the forward and the feedback gain drifting of the system are calibrated online through the adjustment of the digital controller and the reference voltage of the DA-chip, separately. The simulation experiments show that about 90.26% of the gain-drifting could be estimated and about 87.56% of the output error of the accelerate could be restrained. Consequently, the proposed schedules could promote the long-term stability of the Digital-QFA significantly.
Interventions for long‐term software security: Creating a lightweight program of assurance techniques for developers

Though some software development teams are highly effective at delivering security, others either do not care or do not have access to security experts to teach them how. Unfortunately, these latter teams are still responsible for the security of the systems they build: systems that are ever more important to ever more people. We propose that a series of lightweight interventions, six hours of facilitated workshops delivered over three months, can improve a team's motivation to consider security and awareness of assurance techniques, changing its security culture even when no security experts are involved. The interventions were developed after an Appreciative Inquiry and Grounded Theory survey of security professionals to find out what approaches work best. We tested the interventions in a participatory action research field study where we delivered the workshops to three software development organizations and evaluated their effectiveness through interviews beforehand, immediately afterwards, and after twelve months. We found that the interventions can be effective with teams with limited or no security experience and that improvement is long‐lasting. This approach and the learning points arising from the work here have the potential to be applied in many development teams, improving the security of software worldwide.
Occupational therapy practice guidelines for adults with Alzheimer's disease and related disorders

Practice guidelines are important tools for promoting the highest quality of care. In this latest practice guideline from the American Occupational Therapy Association, Occupational Therapy Practice Guidelines for Adults With Alzheimer's Disease and Related Disorders gives occupational therapy practitioners, educators, and health care professionals an evidence-based guideline for providing the best, most appropriate care for adults with Alzheimer's disease and related disorders as well as their caregivers. There are numerous types of dementia; some are rare, but others are reaching alarming proportions and will continue to grow as the world s population ages. The most prevalent is Alzheimer's disease, an irreversible, progressive brain disease causing neuropathological changes in brain tissue, which accounts for 70% of all dementia in older adults. The disease affects those with it, their families, and their communities. An occupational therapy evaluation can inform decision makers about the need and level of support at each stage of the disease. Maintaining quality of life with a progressive condition includes promotion of optimal participation in daily activities. Occupational therapy services can maximize engagement in day-to-day leisure, social, life skills, and self-care activities. Designed primarily for clinical practitioners, Occupational Therapy Practice Guidelines for Adults With Alzheimer's Disease and Related Disorders is a vital reference tool for occupational therapy and occupational therapy assistant students and educators, policymakers, and other health care professionals who work with clients with the disease and their families and caregivers. The guideline clarifies the role of occupational therapy services for external audiences by determining the appropriateness of occupational therapy referrals and detailing the scope of services related to Alzheimer's disease.
Smart medicine for healthier living

SMART MEDICINE FOR HEALTHIER LIVING is a complete A-to-Z guide to the most common ailments and disorders and their treatments, using both alternative care and conventional medicine. This unique book is designed to give you quick and easy access to up-to-date information and advice regarding your personal health and safety. SMART MEDICINE FOR HEALTHIER LIVING is divided into three parts. Part One explains the full spectrum of approaches used to effectively treat health problems. It provides an overview of the fundamentals and uses of conventional medicine, herbal medicine, homeopathy, acupressure, diet, and nutritional supplements. Part Two contains a comprehensive A-to-Z listing of the various health problems--from asthma to the common cold to toxoplasmosis. Each entry in this section clearly explains the problem and offers specific advice using a variety of approaches. Where appropriate, highlighted emergency treatments are included for quick and easy reference. Part Three provides step-by-step guidance on using many therapies and procedures suggested in Part Two--from locating acupressure points to preparing herbal remedies.