Miracle-dz/UniFAR-FTUs huggingface dataset:
A SURVEY ON LEAF DISEASE DETECTION USING IMAGE PROCESSING TECHNIQUES

In the study on leaf disease detection can be a helpful aspect in keeping an eye on huge area of fields of crops, but it’s important to detect the disease as early as possible. Our survey paper mainly focuses on the research oriented techniques which detects the leaf diseases to the earliest and image processing methods have been proposed by the authors which enhances the crop yield thus in stopping various bacterial, virus, fungal and nematodes. Summary of various papers have been drawn, which gives us clear idea on how to improve other parameters which in turn helps us to stop the diseases. Plant disease detection is emerging field in India as agriculture is important sector in Economy and Social life. Earlier unscientific methods were in existence. Gradually with technical and scientific advancement, more reliable methods through lowest turnaround time are developed and proposed for early detection of plant disease. Such techniques are widely used and proved beneficial to farmers as detection of plant disease is possible with minimal time span and corrective actions are carried out at appropriate time. In this paper, we studied and evaluated existing techniques for detection of plant diseases to get clear outlook about the techniques and methodologies followed.
Prevention of Carousal Attack and Stretch Attack in Wireless Sensor Network by using Trust value

—Wireless sensor network is an importantplatform for communication. Wireless ad-hoc sensor network is vulnerable to Denial of Service (DOS) attack. Denial of service attack (DOS) blocks resources and not available to users. This Denial of service attack creates suitable condition for Vampire attack and makes main cause for it. Vampire attack makes the node to consume more battery power and degrades the network performance. Vampire attack does not rely on any particular type of routing protocol. In propose system trust value and energy consumption is calculated for each node to minimize the vampire attack.
Anti TNF-α Therapy in Rheumatoid Arthritis: A New Insight

The development of anti Tumor necrosis factor alpha (TNF-α) therapies is an alternative to the existing treatments of rheumatoid arthritis (RA). These anti TNF-α therapeutics aim to inhibit the inflammatory activities of TNFα, which is the major cytokine causing the disease RA. Biologic agents are the newest forms of drugs to treat RA among the disease modifying anti rheumatic drugs (DMARDs). Though, these biologics do not cure the disease, but certainly slow down the progression of the disease with less risk. There are several monoclonal antibody based drugs and fusion proteins which are found to be remarkably successful in this regard. However, comparing the safety concern and immunogenic reactions of theses therapeutics this review highlights on further improvements and efficacy of these drugs by subsiding the side effects. Keywords-Tumor necrosis factor alpha (TNF-α), anti TNF-α, rheumatoid arthritis (RA), disease modifying anti rheumatic antibody drugs (DMARDS), biologics. ______________________________________________________________________________________________________
Motivated Information Acquisition in Social Decisions∗

Individuals can often inquire about how their decisions would affect others. When do they stop the inquiry if one of their options is preferred based on a selfish motive but is potentially in conflict with social motives? Using a laboratory experiment, we provide causal evidence that having a selfishly preferred option makes individuals more likely to continue the inquiry when the information received up to that point predominantly suggests that the selfish behavior harms others. In contrast, when the information received up to that point predominantly suggests that being selfish harms nobody, individuals are more likely to stop acquiring information. We propose a theoretical model drawing on the Bayesian persuasion model of Kamenica and Gentzkow (2011). The model shows that the information acquisition strategy documented in our experiment can be optimal for a Bayesian agent who values the belief of herself not harming others but attempts to persuade herself to behave self-interestedly. The model predicts that strategic information acquisition motivated by self-interest can reduce the decisions’ resulting negative externalities and improve the welfare of the affected others. Our laboratory experiment indeed confirms this prediction. ∗ Funding by the German Research Foundation (DFG) through CRC TR 224 (Project A1) is gratefully acknowledged. †corresponding author; address: Institute for Applied Microeconomics, University of Bonn, Lennéstrasse 43, 53113 Bonn, Germany; Email: sichen@uni-bonn.de ‡address: Institute for Microeconomics, University of Bonn, Lennéstrasse 43, 53113 Bonn, Germany; Email: heese@uni-bonn.de
Initial training and active teaching methods: the case of the Ecole Normale Supérieure in Casablanca of Morocco

In Morocco, most private middle and secondary schools rely mainly on public teachers to compensate for the lack of pedagogical support in the private education sector. To enable these private institutions to have a stable teaching body, the Ecole Normale Supérieure (ENS) organized educational courses in licenses for the professions of education. As part of this training, several teaching methods are taught. The latter would have a direct impact on students' learning and cannot be dissociated in the context in which they take place (the work climate, the high class size, the availability of teaching and experimental materials, Time management, level of student pre-requisites, teaching experience, etc.). In order to align the initial training with realities in the classroom, we surveyed graduates of the ENS of Casablanca who have already obtained a teaching load and we wanted to know if they use the teaching methods, centred on the student, learned during their initial training in their classes and also what factors restrict the use of these methods? According to the results obtained, only a minority has the opportunity to put into practice and the lecture (masterful or interactive) is always dominated their teaching.
Sweet potato (Ipomoea batatas) vine silage: a cost-effective supplement for milk production in smallholder dairy-farming systems of East Africa?

Context Dairy production in East Africa is dominated by smallholder production systems, but is dogged by suboptimal milk production mediated by poor nutrition. Grain-based concentrates can be used to make the energy and protein deficits in rain-fed systems, but this strategy faces several hurdles. For livestock production systems to be sustainable, it is important that less human-edible food is fed to animals and sweet potato can serve both as a source of human food (tuber) and animal feed (vines). Smallholder scale-appropriate technology has been used to allow feed preservation of the perishable sweet potato vines for use throughout the year. Aims We assessed the efficacy of sweet potato vine silage plus wheat bran (SPVSWB) as a supplement to maintain milk production at a lower cost than that of grain-based commercial dairy concentrate (CDC). Methods Multiparous Holstein–Friesian cattle (n = 12) were given a basal diet of Napier grass (Pennisetum purpureum cv. South Africa), ad libitum, plus a fixed amount of either SPVSWB or CDC, (designed to be both iso-nitrogenous and iso-caloric) during late (LL) and early (EL) lactations. Key results Daily milk yield was lower for SPVSWB than for CDC groups, although comparable (not significant), in both LL (6.2 vs 7.5 L/day) and EL (14.2 vs 16.0 L/day); however, the lower cost of production for SPVSWB (23.2 vs 48.7 KES/kg DM) ensured that margins on milk income over feed (per cow per day) were greater for SPVSWB in both periods. (LL: 71 vs 14.5; and EL: 426 vs 400 KES/day). The lower intake for SPVSWB than for CDC is most probably due to high neutral detergent fibre content in the supplement and the lower milk production, owing to either, or both, of lower energy and protein intake. Conclusions It is suggested that some reformulation of SPVS, replacing in part or in whole the Napier grass with rejected sweet potato tubers, will decrease the neutral detergent fibre content, increase the metabolisable energy content, reducing the need for additional wheat bran and may, thereby, enhance the production response to equate with that of CDC. Implications It is clear that, despite SPVSWB eliciting lower milk production (LL 6.2 and EL14.2 L/day) than does CDC (LL 7.5 and EL 16.0 L/day), SPVSWB is a cost-effective, accessible alternative to grain-based supplementation in small-holder dairy-farming systems of Kenya.
PERSONALIZED RECOMMENDATION FRAMEWORK IN TECHNOLOGY ENHANCED LEARNING

: There is growing consensus that the success of our students and our nation requires the modernization of our education system to be student-centered and personalized. Personalized learning does not require that all learning is digital, but it cannot be achieved at scale without technology. Technology-enabled personalized learning means that technology is used to identify student needs, dynamically customize a playlist of student learning experiences, support teachers
Larvicidal and adulticidal activities of malaysian seaweeds against Aedes Aegypti (L.) and Aedes Albopictus skuse (diptera: Culicidae)

Discovering new mosquitocidal agent is the research focus of government authorities, researchers and industrial investors. Seaweeds serve a great potential in providing unique components and compounds with effective bioactivity. In the present study, seaweed species collected from West Malaysia were evaluated for their larvicidal and adulticidal activities according to WHO guidelines. Extracts were prepared by maceration of dried seaweeds in methanol. Of the 15 species tested, the green seaweed Bryopsis pennata exhibited the strongest larvicidal activity against Aedes aegypti (LC50 value: 156.97 μg/ml) and Ae. albopictus (LC50 value: 177.50 μg/ml). The brown seaweed Sargassum siliquosum had the strongest adulticidal effect against Ae. aegypti (LC50 value: 17.53 mg/cm2) and Ae. albopictus (LC50 value: 35.40 mg/cm2), among the 11 species tested. Larvae and female adults showed signs of intoxication, such as restless movement, tremor, paralysis, and followed by eventual death, after exposure of the seaweed extract. Future investigation on the active component and mode of action of the seaweed extracts should be carried out.
China's future healthcare system: what role for private production and financing?

In China, the private sector may make healthcare markets more competitive, thereby improving affordability, increasing the supply and quality of healthcare services and improving the accessibility to healthcare. It can also improve financial coverage via private health insurance, as a substitute or complement to government plans. However, strict regulation, insurance designation bias against private hospitals, insufficient risk-management capacity and crowding out by social health insurance have hampered private sector involvement in health services production and insurance. We argue that the best option at China's current state of development may be a compromise model in which competing private providers are given an important role, but in which the government intervenes in such a way as to attain both a high degree of equity of access to healthcare, and to avoid the most significant forms of 'market failure' in an unregulated private system.
Sentiment Classification and Analysis on Arabic using Semi-Supervised Approach

: Classification and analysis of Arabic text in terms of social media analysis is presented here in this work. This work, keeping in view the morphological and syntactical difficulties in Arabic language, focuses on negative and positive sentiment candidates for polarity as a first step towards a major goal of building a complete framework for political sentiment analysis. There are many works for sentiment classification and analysis in literature, which can be categorized into supervised, unsupervised, and hybrid. However, majority of these methods either lack in availability of sufficient size dataset for learning or suffer from Arabic language complications in terms of processing diverse nature of text. To overcome this issue, we introduce a semi-supervised approach for sentiment classification and analysis in Arabic language. Our approach is based on the concept of word embedding model to improve the performance of classification even with small size seed data. It has the capability to model the words in a large vector space where similar words are expected to occur in close proximity. Once the data is mapped to vector space model, then we utilize various classifiers to learn the patterns in the lexicon and predict the classification as positive or negative for unknown similar words. Classifiers such as Stochastic Gradient Descent and SVM are trained and tested with the specified 80% and 20% data ratio. Our approach yields around 80% accuracy through intermediate experiments. It has been observed that besides the common problem of lexicon size, this is attributed mainly to the quality of word embedding available for the Arabic language.
STUDENT VERSION Enabling Epidemic Exploration Education

While working with the principal author of [3] to prepare the essence [6] of a modeling scenario on the basic SIR model for epidemics for wider use than as a project in the author’s class we became aware of several interesting possibilities. Since [3] presents a modeling opportunity with data obtained and cited in [1, 5] we explored the several routes to parameter estimation in the SIR model with respect to the data pictured in [1] and offered in Table 1.
ANALYTIC FRAMEWORK FOR SOCIAL OPINION PREDICTION OF ONLINE NEWS BASED ON SENTIMENT ANALYSIS

: In today’s world everything available on the internet because of the digital era. With the fast development of web, peoples spent their most time on internet. Recently, in social platforms new function introduced in which user may select one emotion out of many choices, to express their opinion more precisely. For this tasks the social emotion mining technique is used. This is the most important and widely used in social platforms and businesses alike. In history, lots of work has been done of social emotion mining from author’s perspectives. Recent research focuses on reader’s emotions with news articles. In existing system Social Opinion Mining is developed which predict the reader’s emotions of news based on the social opinion network. The construction of opinion network based on the semantic distance between two words. In existing system model for analysis of news the system do various comparisons which is time consuming. Therefore, in proposed system we are going to develop an Intellectual Sentiment Analytic Model for the social opinion prediction. Due to Sentiment analysis the Intellectual Sentiment Analytic Model reduced time to large extent and effective results constructed as compared to the state of the art model.
Reason Analysis for Suspension/Early Termination of Drug Clinical Trial

Object To collect a scientific basis for improving the quality and success rate of drugclinic al trials by analyzing the reasons for the suspension or termination of clinical trials in China and abroad. Method Drug Clinical Trials Registration and Information Disclosure Platform (chinadrugtrials.org.cn) and ClinicalTrials.gov (www.clinicaltrials.gov) were searched from August 1,2007 to August 1, 2017. Searches were conducted using the status “suspended” or“terminated”. Result From August 1, 2007 to August 1, 2017, the drug clinical trials of total items of which 6.30% were suspended/terminated prematurely. In the main type, by comparing the cause on Chinese and foreign clinical trials to suspend/early termination type, the results show that the two groups are similar distribution. By comparing the causes of subtypes, the most common reason for the termination of clinical trials abroad is the difficulty of recruiting subjects. The most common cause of suspension of domestic clinical trials is the decision of the sponsor. Conclusion About 59.09% of the clinical trials were due to nothing to do with the test data to suspend or early termination. While reasons are corrected, we can take the initiative to minimize the probability of clinical trials to be suspended.
IN CHILDREN IN THE ABSENCE OF SIGNIFICANT CLINICAL SYMPTOMS AND SIGNS

Objectives: To determine the frequency of vitamin D deficiency in children under 12 years of age in the absence of significant clinical signs and symptoms in an ambulatory care settings. Study Design: Descriptive study. Settings and duration: This study was conducted in Pediatric Out Patient Department of KAUH from June 2013 to June 2014. Materials and methods: Patients attending the pediatric clinic in KAUH Riyadh, KSA, from June2013 to June 2014, in which 287 healthy children under 12 years were enrolled. Serum calcium, phosphorus, alkaline phosphatase and 25-hydroxyvitamin D [25(OH) D] were measured . X ray wrists were taken for radiological evidence of rickets. 25(OH) D levels <50 ng/mL and <25 ng/mL were defined as insufficiency and severe vitamin D deficiency, respectively. Results: A high prevalence of vitamin D deficiency is observed in healthy children even in absence of clinical signs and symptoms. The problem should be highlighted and there is a need to create awareness among people about the etiology of vitamin D deficiency and its prevention.There is a strong need for long term planning including populationscreening, dietary supplementation with vitamin D and food fortification.
Hybrid/Doped Carbon-Based (Nano)materials for Advanced Applications: o-Sustainable Catalysis, Biomass Valorization, Energy Technologies & Smart Devices

Carbon-based (nano)materials are remarkable building blocks that have been boosting innovation in a multitude of advanced applications, ranging from Catalysis and Environment to Energy and Smart Technologies. Our research group from the Associated Laboratory for Green Chemistry REQUIMTE/LAQV, at the Chemistry and Biochemistry Department of Faculty of Sciences of Porto University, Portugal, has been developing research work within the context of R&TD projects in the areas of hybrid and doped carbonbased (nano)materials for eco-sustainable catalysis, biomass valorization, energy technologies and smart devices. In this article, the main achievements and progress in these fields are reviewed.
Segmentation of Vestibular Schwannoma from Multi-parametric Magnetic Resonance Images using Convolutional Neural Network

In this study, we aim to automatically segment the Vestibular Schwannoma (VS) from multi-parametric magnetic resonance (MR) images before the Gamma Knife (GK) treatment using the deep learning based Convolutional Neural Network (CNN). 516 VS subjects' MR images and tumor contours were collected from Taipei Veteran General Hospital, Taiwan. All the MR images were scanned by 1.5 T GE scanner. The tumor contours were delineated manually by experienced neuroradiologists. MR images included 1) 1) T1- weighted (T1W) with matrix size 512 x 512, voxel size 0.5 x 0.5 x 3mm;2) T1- weighted gadolinium contrast-enhanced (T1W+C) with matrix size 512 x 512 and voxel size 0.5 x 0.5 x 3mm; 3) T2 - weighted (T2W) with matrix size 512 x 512, voxel size 0.5 x 0.5 x 3mm. Since some tumors consisted of solid part, which appeared as high intensity at T1W+C, and cystic part, which appeared as high intensity at T2W, we used multi-parametric MR images and designed a deep learning based encode-decode CNN model with two convolution pathways and different convolution kernel sizes at encode part to extract feature maps from different direction of anisotropic voxel-size MR images. Our results showed that the multi-parametric input, namely, T1W, T1W+C and T2W images, for the proposed CNN achieved superior performance with Dice coefficient = 0.87±0.06 in the segmentation of VS, especially for tumors with cystic components, compared to using the single-parametric input T1W+C image with Dice coefficient = 0.83±0.11.
Distributed salinity sensor based on Brillouin dynamic grating

The distributed measurement of salinity is experimentally demonstrated by Brillouin dynamic grating (BDG) The position-resolved salinity change can be measured by mapping the birefringence change through the BDG, where the salinity altering can induce the swelling or shrinking actions of the PI coating through absorbing or releasing water. Four sensors with the coating thickness of 5 μm, 8 μm, 15 μm, and 20 μm were fabricated as demos to characterize the salinity sensitivity of the sensors, with 30.1 MHz/(mol/L) for 5 μm, 75.4 MHz/(mol/L) for 8 μm, 119.2 MHz/(mol/L) for 15 μm, and 139.6 MHz/(mol/L) for 20 μm, respectively. The proposed sensor shows a linear and reproducible response to the salinity change, and its measurement uncertainty is less than 10 MHz, corresponding to the obtained maximum salinity accuracy of 0.072 mol/L.
Full-Chip Electro-Thermal Coupling Extraction and Analysis for Face-to-Face Bonded 3D ICs

Due to the short die-to-die distance and inferior heat dissipation capability, Face-to-Face (F2F) boned 3D ICs are often considered to be vulnerable to electrical and thermal coupling. This study is the first to quantify the impacts of the electro-thermal coupling on the full-chip timing, power, and performance. We first present an implementation flow for realistic F2F 3D ICs including pad layers and power grids. Then, we propose our signal integrity analysis, parasitic extraction, and thermal analysis flows. Next, we investigate the impacts of the coupling on the delay, power, and noise of F2F 3D ICs, and provide guidelines to mitigate these effects. Our experimental results show that the inter-die electrical coupling causes up to 5.81% timing degradation and 4.00% noise increase, while the thermal coupling leads to less than 0.41% timing degradation and nearly no noise increase. The impact of the combined electro-thermal coupling on delay and noise reaches 6.07% and 4.05%, respectively.
Dynamics of water trapped in transition metal oxide-graphene nano-confinement

Motivated by practical implementation of transition-metal oxide-graphene heterostructures, we use all atom molecular dynamics simulations to study dynamics of water in a nano slit bounded by a transition metal oxide surface, namely, TiO2 termination of SrTiO3, and graphene. The resultant asymmetric, strong confinement produces square ice-like crystallites of water pinned at TiO2 surface and drives enhanced hydrophobicity of graphene via the proximity effect to the hydrophilic TiO2 surface. This importantly brings in dynamic heterogeneity, both in translational and rotational degrees of freedom, due to coupling between the slow relaxing, strongly adsorbed water layer at the hydrophilic oxide surface, and faster relaxation of subsequent water layers. The heterogeneity is signalled in the ruggedness of the effective free energy landscapes. We discuss possible implications of our findings in drug delivery.