Miracle-dz/UniFAR-FTUs huggingface dataset:
Molecular characterization and tissue distribution of cysteamine dioxygenase (ADO) in common carp Cyprinus carpio

The low production of hypotaurine from cysteine but a significantly high taurine deposition in common carp led to the hypothesis that this species utilizes an alternative pathway other than the cysteine sulfinic acid pathway. Cysteamine pathway is common in mammals but not in other animals such as birds, invertebrates, and fishes. The cloned cysteamine dioxygenase (ADO) cDNA in common carp consists of 790 nucleotide bases with 260 deduced amino acid sequence. The conserved domain is the DUF1637 which has a conserved tyrosine and cysteine residues and the presence of three predicted N-glycosylation sites. Phylogenetic analysis using neighbor joint method indicated that ADO in common carp branched after Sinocyclocheilus rhinocerous. ADO was expressed in hepatopancreas, brain, gill, intestine, and muscle of common carp. The hepatopacreas had a significantly higher gene expression level than the other organs examined. The present results suggest that ADO is present in common carp.
A Noninvasive Assistant System in Diagnosis of Lumbar Disc Herniation

The purpose of this study is the application of pressure sensors in diagnostics and evaluation of the accuracy diagnostics of lumbar disc herniation at levels L4/L5 and L5/S1 using the aforementioned platform. The motivation behind the idea to apply the pressure measurement platform is the fact that the motor weakness of plantar and dorsal flexia of the feet is one of the absolute indications for the operative treatment of patients with lumbar disc herniation at the indicated levels. In patients, MRI diagnosis of the lumbosacral spine served as the ground truth in the diagnosis of herniation at L4/L5 and L5/S1 levels. The inclusive criteria for the study were the proven muscle weakness based on manual muscle tests performed prior to surgery, after seven days of surgery and after physical therapy. The results obtained with the manual muscular test were compared with the results obtained using our platform. The study included 33 patients who met the inclusion criteria. The results of the measurements indicate that the application of our platform with pressure sensors has the same sensitivity diagnostics as a manual muscle test, when done preoperatively and postoperatively. After physical therapy, pressure sensors show statistically significantly better sensitivity compared to the clinical manual muscle test. The obtained results are encouraging in the sense that the pressure platform can be an additional diagnostic method for lumbar disc herniation detection and can indicate the effectiveness of operative treatment and physical therapy after operation. The main advantage of the system is the cost; the whole system with platform and sensors is not expensive.
Benefits and Risks of Shadow Money: Evidence From the Chinese WMP Market

We study banking competition in presence of shadow money. Investors choose between insured deposits and uninsured off-balance sheet shadow money. Banks compete for investors by setting corresponding interest rates and default endogenously. Our approach allows to quantitatively examine the benefits and risks inherent in shadow money across time and states. We calibrate our model to Chinese banking sector data using wealth management products (WMPs) as proxy for shadow money. Implicit guarantees inherent in WMPs incentive banks to issue more shadow money. The resulting supply of credit boosts economic growth but also builds up financial fragility that potentially hampers economy. Multiple equilibria emerge which may lead to severe financial distress with large welfare losses. Further, we show that banks are more fragile if adjusting rates on shadow money is costly and that imposing capital requirements on shadow money is not a suitable policy to enhance stability.
GLOBAL SYMPOSIUM ON SOIL ORGANIC CARBON, Rome, Italy, 21-23 March 2017 Soil carbon models for carbon stock estimation – where do we fail?

Soil organic carbon (SOC) stock change estimates are needed in order to understand CO2 exchange between atmosphere and biosphere. Repeated nationwide SOC inventories are rare and expensive. In the absence of soil inventories, models are used to estimate SOC changes. These models are applied widely with GHG inventories under UNFCCC and with earth system models (ESM), e.g. for IPCC assessment reports. Soil carbon models simplify complex processes and often lack history of soils in a given region. Therefore, it is not surprising that these models fail as sub-modules of ESMs (Guenet et al. 2013, ToddBrown et al. 2013). The major reason for poor performance of SOC models results from the uncertainty with steady state SOC stock for model initialization. Here we compare different soil carbon models (Yasso07, ROMULv, Century and Q) against Finnish and Swedish SOC inventories and we identified conditions under which these models fail. We also analyzed SOC outputs of ESMs and compared those to global SOC databases. We found that models were failing on nitrogen rich sites, we also found underestimation of SOC stocks on water limited sites and on those with excess water. Our findings provide directions for modelling community in order to further improve models and their ability to quantify SOC stocks.
Blind Motion Deblurring Using Non-edge Specific Adaptive Scheme

: Deconvolution of a true image from a degraded image from unkown blur kernel is blind image deconvolution. In real life application, assuming a known kernel for deblurring is not a suitable solution. Existing methods are not robust , in this case an algorithmic approach to combined blur identiﬁcation and image rebuilding is essential. This paper mainly focus on effective method of blind motion deblurring toward image diversity. This method is a combination of two schemes, edge speciﬁc and nonedge speciﬁc scheme.Such a combination is a new approach in every aspect. A prediction and detection method comes under edge speciﬁc scheme. It is sensitive to diversity of edges of present in natural pictures. Different images have different statistical composition, non-edge speciﬁc scheme is sensitive to these statistical variations. A novel non-edgespeciﬁc adaptive scheme (NEAS) is proposed,which work well on diversity of natural images. NEAS can highlight the features from both edge speciﬁc and non-edge speciﬁc schemes. The performance of NEAS is compared against state-of-art using a very large image set.
The construction and analysis of competitive endogenous RNA (ceRNA) networks in metastatic renal cell carcinoma: a study based on The Cancer Genome Atlas

Background The pathogenesis of metastatic renal cell carcinoma (mRCC), one of the most common malignant neoplasms, remains unknown. Studies on competitive endogenous RNAs (ceRNAs) have uncovered new interactions between RNAs, which suggest their roles in cancer pathogenesis. However, the role of ceRNA networks in mRCC has not yet been studied. Thus, this study aims to explore the role of ceRNA networks in mRCC development and identify potential prognostic indicators. Methods We analyzed RNA sequencing data of mRCC patients, which had been obtained from The Cancer Genome Atlas (TCGA) database. Next, differentially expressed long-noncoding RNAs (DElncRNAs), differentially expressed micro RNAs (DEmiRNAs), and differentially expressed messenger RNAs (DEmRNAs) in mRCC and clear cell RCC (ccRCC) samples were identified using the edgeR package that is available in R software. Moreover, based on the Database for Annotation, Visualization, and Integrated Discovery (DAVID), enrichment analyses for biological processes and pathways functional were performed. As such, we built a ceRNA network and performed a survival analysis using the survival package in R. Results A total of 369 DElncRNAs, 12 DEmiRNAs, and 728 DEmRNAs were identified for further analysis. Of these, 11 lncRNAs, 20 mRNAs, and 2 miRNAs were included in the ceRNA network. Moreover, 7 of the 11 lncRNAs and 3 of the 20 mRNAs were associated with the overall survival of mRCC patients (P<0.05). Conclusions Collectively, our findings allow a deepened understanding of the molecular mechanism of the ceRNA network and its role in mRCC development, which can guide both mRCC therapy and related future research.
Alacart: Poor Man’s Classification Trees

2 Bruce Erlichman’s inventiveness deserves kudos for the name Alacart. His alternative, Magna Cart, might be used in the future. We will concentrate on binary classification of a dependent (0,1) Y x 1) variable. Label the 0’s as ‘bad’, and the 1’s as ‘good’. Assume that the proportion of 0’s is 50%. In this case of no majority, it is not possible to classify the initial data set as either good or bad according to Y. Were the proportion of “bads” 30%, say, the initial data set would be classified as “good”.
Perceptions and Career Choices Linked to the UAE Youths Entrepreneurial Intention

The purpose of this research is to gain insights on the entrepreneurial intentions of UAE youths. A sample of 303 students (over 15 years of age) from UAE based schools and higher educational institutions were surveyed using a questionnaire to gauge their perspective on choosing entrepreneurship as a career. Three main categories of factors influencing their career choices were taken into account, namely their socioeconomic status, familial background and personality traits. The analysis that follows breaks down the explained entrepreneurial intention into ‘Perception of Entrepreneurship in Society’ and ‘Preference for Entrepreneurship as a Career Choice’ in order to develop a causal relationship between how the UAE youth perceives entrepreneurs around them and how that influences their aspirations to opt for the same as a career choice upon completion of their education. Linkages between demographic factors (like age, gender and nationality), socioeconomic status and family background have been taken into account in the first two sections where their influence on the said perception and preference is analysed. In the third section of this analysis, the correlation between the Big Five personality traits and entrepreneurial intent of the youth is assessed, in order to identify which of these five personality traits have the strongest influence on a young individual’s perception of entrepreneurial activities and the consequent decision to choose entrepreneurship as a preferred career path. The study will assist in reducing the youth unemployment through the development of sustainable entrepreneurial culture and ventures in the United Arab Emirates and Gulf Cooperation Council (GCC) countries as a whole due to its homogenous socio-cultural and economic context.
A Biometric Model for Examination Screening and Attendance Monitoring in Yaba College of Technology

—Examination malpractices have consistently remained a bane of Nigerian educational system. A common form of examination malpractices is the deliberate impersonation of the applicant. Part of the requirement of a credible examination is that the real applicants wrote the exams. Several steps have been taken to check this crime unabated. Some of the methods adopted are: the use of Identity card; the presence of invigilators to identify fake students; the allocation of sitting arrangement number that determines the hall where the student will write exam and the need to sign in and out on the attendance sheets. This research work proffers solution to the problem of student impersonation during exams. A biometric model is designed to identify every applicant at the point of entry into the examination hall. A biometric verification exercise is also conducted while the examination is going and at the point of submission of examination papers. The students’ attendance is captured automatically as their identity is verified on the biometric systems. The Biometric Access Control Techniques is explained. A model describing its application to examination screening and attendance monitoring is designed using denotational mathematics.
INVERSE CHARACTERIZATION OF SANDWICH STRUCTURES USING SINGLE-SHOT WAVE SPEED MEASUREMENTS

We propose an innovative method for the local inverse characterization of sandwich panels using a simple experimental procedure based on single shot pulse measurements. The method exploits a typical wave conversion phenomenon called bending-to-shear transition, producing a local energy velocity maximum within the transition bandwidth. Analytic expressions are derived for the first wave transition and used to retrieve skin’s tensile modulus and equivalent honeycomb core’s shear modulus from the transition frequency and the maximal group velocity. A simple iterative procedure is described to identify the transition frequency by comparison of the time delays between the pulse source and single measurement point. The group velocity can then be advantageously estimated using First Phase Arrival (FPA) times. A carbon fiber-reinforced sandwich panel with Nomex honeycomb core is considered for case study. The proposed method exhibits considerably reduced measuring and post-processing times, while experimental results are in good agreement with static measurements and the results from the Inhomogeneous Wave Correlation (IWC) method. MEDYNA 2017 25-27 Apr 2017, Sevilla (Spain)
Preprocessing Unevenly Sampled RR Interval Signals to Enhance Estimation of Heart Rate Deceleration and Acceleration Capacities in Discriminating Chronic Heart Failure Patients from Healthy Controls

Objective. The deceleration capacity (DC) and acceleration capacity (AC) of heart rate, which are recently proposed variants to the heart rate variability, are calculated from unevenly sampled RR interval signals using phase-rectified signal averaging. Although uneven sampling of these signals compromises heart rate variability analyses, its effect on DC and AC analyses remains to be addressed. Approach. We assess preprocessing (i.e., interpolation and resampling) of RR interval signals on the diagnostic effect of DC and AC from simulation and clinical data. The simulation analysis synthesizes unevenly sampled RR interval signals with known frequency components to evaluate the preprocessing performance for frequency extraction. The clinical analysis compares the conventional DC and AC calculation with the calculation using preprocessed RR interval signals on 24-hour data acquired from normal subjects and chronic heart failure patients. Main Results. The assessment of frequency components in the RR intervals using wavelet analysis becomes more robust with preprocessing. Moreover, preprocessing improves the diagnostic ability based on DC and AC for chronic heart failure patients, with area under the receiver operating characteristic curve increasing from 0.920 to 0.942 for DC and from 0.818 to 0.923 for AC. Significance. Both the simulation and clinical analyses demonstrate that interpolation and resampling of unevenly sampled RR interval signals improve the performance of DC and AC, enabling the discrimination of CHF patients from healthy controls.
Acoustic Sensor Network for Surveillance and Target Acquisition of Terrestrial Military Operations

—The main objective of this work is to present a system that detects and identiﬁes combat vehicles with a wireless sensor network that contains acoustic sensors. The objective is to gather the sound from the combat vehicles, with acoustic sensors in the nodes of the wireless sensor network, perform the classiﬁcation of the vehicle in the node and then send the packet to the base station using packet routing and data aggregation. The data base of vehicle sounds, drawn from combat vehicles of the Armed Forces, was made by training Gaussian mixture models (GMM) with data that explores the spectral characteristics of the sound, Mel Frequency Cepstral Coefﬁcients (MFCC) and Beats per minute (BPM) were used as observation data. Vehicle detection and identiﬁcation is performed with a GMM classiﬁer. The NS3 simulator was used to simulate the wireless sensor network and the respective data aggregation and routing. The routing protocol used is DSDV, and it was tested over two different technologies, IEEE 802.15. 4 and IEEE 802.11g. For the tests of the classiﬁer, the number of Gaussian mixtures was optimized and the tests were made with different time windows for the MFCC. It was concluded that the classiﬁer is better without the rhythm detection, that is, using only the MFCC it can obtain an F-score of 0.875 with eight combat vehicles on the data base. The simulations done using the NS3 simulator indicate that there must be a trade-off between the delays, the radio range and power consumption. The 802.15. 4 technology, with aggregation, would be the most appropriate choice to the case study. However if it is desired to cover big areas, because of tactical restrictions, the most suitable technology is 802.11g.
Stained images of Brodmann's area 45 in the left and right hemispheres of a human brain. Sections were stained using a modified Gallyas stain for Nissl

The human brain shows marked gross anatomical and microstructural asymmetries that are presumably related to lateralized motor and cognitive functions. This chapter generally summarizes the extant data on gross morphological asymmetries in human and nonhuman mammal brains. In addition, the evidence of microstructural asymmetries, such as gray-level index, minicolumn width, and cellular organization, are presented. Although there are few studies of microstructrual asymmetries in nonhuman primates, it is argued that such studies are important for validating morphological asymmetries as well as for understanding the cellular basis for hemispheric specialization in primates,
Ephedrine production from suspension cultures of Ephedra alata L. callus

Ephedra alata is an important Egyptian medicinal plant with enormous applications in pharmaceutical industry. Shake-flask suspension cultures of E. alata were established from internodal segment-derived callus. The suspension cultures were treated with two biotic elicitors, namely Aspergillus niger and yeast extract, to enhance the synthesis of ephedrine – the bioactive constituent of E. alata. Ephedrine was quantified using the high performance liquid chromatography technique. Ephedrine concentration was not directly related to biomass production. Aspergillus niger and yeast extract enhanced the production of ephedrine by 2.5to 7-fold after different durations of incubation as compared to ephedrine content in the mother plant. Treatment with the fungal elicitor A. niger extract induced the maximum accumulation of ephedrine at the concentration of 1.67%; it also increased ephedrine biosynthesis by 7-fold in 24-day-old culture as compared to the ephedrine content in the mother plant and caused higher ephedrine biosynthesis than that in the control treatment without elicitors. The present protocol could be applicable for the large-scale production of ephedrine from E. alata.
Iot Based Supply Chain Traceability Using Enhanced Naive Bayes Approach For Scheming The Food Safety Issues

: Food is one of the major needs for human to live. The worldwide food issue consists of the need of food provision for the Earth's population. Food has to undertake numerous troubles like changing climate, food safety, low nutritive value, etc. Due to the rising demand for fruits and vegetable for daily procedure by the consumers there is necessitate for smarter operation of Food Supply Chain(FCS) and also bond the producer to the customer with delivery of high quality of food products. This paper examines the design and improvement of an Internet of Things (IoT) construction that helps suppliers to manage their procedures of food safety and also tackle the food safety problems from the technological aspect, people require a trustworthy food traceability system that can follow and observe the full lifespan of food manufacture, counting the processes of food raw material farming/reproduction, processing, transporting, warehousing, and wholesale etc. The most important goal of this IoT outline is to sense food characteristics and guidance suppliers to insist farmers properly grow and treat the crops. Using the analysis of fictional data for FSC, deriving a solution for the distribution of distinguished goods with the aid of the Naive Bayes classifier which is used for food traceability enables tracking and management throughout the entire process such as manufacturer, exporter and customer. The structure organizes a collection of IoT nodes arranged in the transporting for sensing food parameters and the RF communication of IoT node is used to transmit the measured data to server. The experimental study of the proposed technique is measured based on time of execution, comparison of accuracy, and rate of error. Prospective strategies were experimented with using the RStudio IDE as the working platform with Java.
Local Gray World Method for Single Image Dehazing

Images taken outdoors are often degraded by atmospheric conditions such as fog and haze. These degradations can reduce contrast, blur edges, and reduce saturation of images. In this paper we propose a new method for single image dehazing. The method is based on an idea from color constancy called the gray world assumption. This assumption states that the average values of each channel in a picture are the same. Using this assumption and a haze degradation model we can quickly and accurately estimate the haze thickness and recover a haze free image. The proposed method is validated on a synthetic and natural image dataset and compared to other methods. The experimental results have shown that the proposed method provides comparable results to other dehazing methods.
Charged skyrmions and topological origin of superconductivity in magic-angle graphene

Pairing from topology explains superconductivity in magic-angle graphene and predicts other unconventional superconductors. Topological solitons, a class of stable nonlinear excitations, appear in diverse domains as in the Skyrme model of nuclear forces. Here, we argue that similar excitations play an important role in a remarkable material obtained on stacking and twisting two sheets of graphene. Close to a magic twist angle, insulating behavior is observed, which gives way to superconductivity on doping. Here, we propose a unifying description of both observations. A symmetry breaking condensate leads to the ordered insulator, while topological solitons in the condensate—skyrmions—are shown to be charge 2e bosons. Condensation of skyrmions leads to a superconductor, whose physical properties we calculate. More generally, we show how topological textures can mitigate Coulomb repulsion and provide a previously unexplored route to superconductivity. Our mechanism not only clarifies why several other moiré materials do not show superconductivity but also points to unexplored platforms where robust superconductivity is anticipated.
Threshold of primordial black hole formation in nonspherical collapse

We perform (3+1)-dimensional simulations of primordial black hole (PBH) formation starting from the spheroidal super-horizon perturbations. We investigate how the ellipticity (prolateness or oblateness) affects the threshold of PBH formation in terms of the peak amplitude of curvature perturbation. We find that, in the case of the radiation-dominated universe, the effect of ellipticity on the threshold is negligibly small for large amplitude of perturbations expected for PBH formation.