Miracle-dz/UniFAR-FTUs huggingface dataset:
Análisis de las relaciones tróficas en un lago de inundación de la Amazonia Colombiana

To determine the trophic relationships in a floodplain lake, we studied the Lake Yahuarcaca (Colombian Amazon), two kilometers west of the city of Leticia, which has the characteristics of a floodplain. During the period of low water hydrological developed an intensive survey of all the environmental compartments of the system include: coastal, benthic, and pelagic regions, riparian vegetation and birds. With this data, complementing with literature information, we construct the food web of the system. Seventy seven taxa were found according to his eating habits and were grouped in twenty two trophospecies, corresponding to four trophic levels. Within the topological characteristics of the network we established fourty links, a value of 0.082 connectance, two relationships of omnivory, two cases of cannibalism. A proportion of 23% of basal trophospecies, within which the detritus is included by functional analogy with producers; 59% of intermediate trofoespecies defined as species that are prey and predator in the system, and finally; 18% of top trophospecies, with no predator identified in the system, and are represented by carnivorous birds and some macroinvertebrates. The food web constructed permit to visualize energy relations between the body of water and the surrounding system, while allowing hypotheses about trophic pathways that sustain fish production in the lake Yahuarcaca, highlighting the importance of detritivore path, with few levels has highly efficient trophic flow in lakes of tropical flood.
Predictors of outcome of cerebral venous sinus thrombosis at a tertiary care centre in Central India

Cerebral venous sinus thrombosis (CVST) is a less common cause of stroke when compared to arterial thrombosis but its clinical presentation is varied and atypical. Early diagnosis may prevent morbidity & mortality which in untreated cases has been reported as 13.8 -48%. Materials and Methods: This prospective observational study included 40 radiologically diagnosed cases of CVST, to evaluate the predictors of outcome by using modified Rankin’s Scale (mRS). The primary outcome measure was death or dependency at the end of 12 weeks. Results: Of 40 patients, 18 cases (45.5%) had mRS 0-3 & 22(55%) had mRS >3. Mean age of the cases was 32.22 yrs with M:F= 1: 0.81. Purperium was the commonest risk factor. In univariate analysis, Age>30(p==0.10), Coma (p=0.010) and Cheyne stokes breathing (p- 30, cerebral haemorrhage and Deep venous sinus thrombosis were the predictors of poor outcome. Rankin’s score of < 2 had good prognosis at 12 weeks follow up. Overall mortality was 15% at 12 weeks follow up. Conclusion: CVST is an important cause of stroke in puerperium. Neuroimaging plays pivotal role in diagnosis. Modified Rankin’s scale is a simple score system risk stratification of patients with neurodeficit. Low MRS score at hospitalization is associated with better outcome at 12 weeks. Keywords: Cerebral venous sinus thrombosis (CVST), modified Rankin’s scale (mRS) < 2, good outcome.
Analysis of Proof-of-Work-Based Blockchains Under an Adaptive Double-Spend Attack

In this article, we study the performance of blockchains by analyzing the common prefix depth, chain quality coefficient, and chain growth speed coefficient. These three parameters characterize the liveness and consistency of transactions which are important for the proper operation of the blockchain. We examine how these three parameters are affected under an adaptive double-spend attack (ADSA). To maintain the performance of a blockchain against ADSA, the user nodes can use a larger number, <inline-formula><tex-math notation="LaTeX">$z$</tex-math></inline-formula>, of confirmation blocks for validating a transaction. A comparison of the values of <inline-formula><tex-math notation="LaTeX">$z$</tex-math></inline-formula> needed to achieve a given target probability of successful attack is provided for ADSA and the traditional double-spend attack with different system models. The results indicate that a larger value of <inline-formula><tex-math notation="LaTeX">$z$</tex-math></inline-formula> is required under ADSA. A more realistic reward model for attackers is also introduced. It is found that the expected reward of an attacker decreases rapidly to zero as <inline-formula><tex-math notation="LaTeX">$z$</tex-math></inline-formula> is increased.
Socioeconomic impact of cervical Spinal Cord Injury (SCI) operated in patients with lower income group

We read the article titled, “Socioeconomic impact of cervical spinal cord injury (SCI) operated in patients with lower income group. ”[1] Being a medical and psychiatric social work practitioner working in mental health, neurosurgery, emergency, and trauma care setting in a tertiary care hospital, I would like to congratulate and appreciate the conscientious and scientific observations made by the authors.
iFinger: Intrusion Detection in Industrial Control Systems via Register-Based Fingerprinting

Nowadays, the industrial control system (ICS) plays a vital role in critical infrastructures like the power grid. However, there is an increasing security concern that ICS devices are being vulnerable to malicious users/attackers, where any subtle changing or tampering attack would cause significant damage to industrial manufacturing. In this paper, we propose the iFinger, a novel detection approach designed to mitigate ICS attacks adapting to various industrial scenes. We take advantage of an important insight that industrial protocol packets include register status values that are used to reflect the physical characteristics of ICS controllers. The iFinger utilizes register states to generate ICS fingerprints to detect malicious attacks on industrial networks. Specifically, the boolean logic represents every register state sequence of the ICS controller, and the deterministic finite automaton (DFA) generates a device fingerprint. To discover the ICS attacks, we propose two detection approaches based on device fingerprints, including passive and active detection. We present a prototype of the iFinger and conduct real-world experiments to validate its performance. Results show that our approach achieves 97.1% F1 score in ICS device identification. Furthermore, we simulate two typical ICS attacks (replacement and code modification) to validate the effectiveness of our iFinger in industrial networks. Our device fingerprints would detect those malicious attacks within 2s latency at 98.0% recall.
PM2.5 Estimation Based on Image Analysis

For the severe haze situation in the Beijing-Tianjin-Hebei region, conventional fine particulate matter (PM2.5) concentration prediction methods based on pollutant data face problems such as incomplete data, which may lead to poor prediction performance. Therefore, this paper proposes a method of predicting the PM2.5 concentration based on image analysis technology that combines image data, which can reflect the original weather conditions, with currently popular machine learning methods. First, based on local parameter estimation, autoregressive (AR) model analysis and local estimation of the increase in image blur, we extract features from the weather images using an approach inspired by free energy and a no-reference robust metric model. Next, we compare the coefficient energy and contrast difference of each pixel in the AR model and then use the percentages to calculate the image sharpness to derive the overall mass fraction. Furthermore, the results are compared. The relationship between residual value and PM2.5 concentration is fitted by generalized Gauss distribution (GGD) model. Finally, nonlinear mapping is performed via the wavelet neural network (WNN) method to obtain the PM2.5 concentration. Experimental results obtained on real data show that the proposed method offers an improved prediction accuracy and lower root mean square error (RMSE).
A parallel algorithm for pricing American options under stochastic volatility

In this thesis a simple, fast and accurate iterative algorithm for pricing American options and solve for its early exercise boundary under a stochastic volatility setup is proposed. The algorithm is based on a fixed-point iteration that is derived from the early exercise representation of American options, and is equivalent to a multivariate Newton iteration that converges globally. This thesis is an extension of the work done by Medina (2013) on the application of the algorithm on the pricing of American options under the Black & Scholes model. The method is stable, robust, converges monotonically, and is well suited for parallel calculations and programming. The algorithm is tested using the Heston stochastic volatility model, and find that the procedure outperforms existing methodologies in terms of pricing efficiency and precision in the calculation of the early exercise frontier. In addition to a CPU implementation similar to what was done in Medina (2013) for the Black & Scholes model, we take advantage of the method’s parallel nature and do a GPU implementation under the Heston model in order to assess its real benefits and surpass other benchmark methods.
How to produce a systematic review

As systematic reviews aim to collate all of the relevant information, clinicians or researchers can be confident that most, if not all, the relevant papers have been considered (Higgins and Green, 2011). Systematic reviews are the most highly regarded research evidence, and therefore, are used to inform guidelines, summarise evidence and provide justification for commencing a randomised controlled trial (Fig. 1) (Murad et al., 2016). I am interested in the long-term risks that follow a diagnosis of gestational diabetes (GDM). Currently, I am synthesizing studies of interventions to reduce the risk of type 2 diabetes (T2D) in women with prior GDM. This review article will form the basis of further research to inform the development of interventions to reduce the risk of T2D. The purpose of this short report is to share the challenges and techniques I have discovered while undertaking a systematic review.
Structural studies on actin-ADP ribosylating binary toxin from C. difficile

Clostridium difficile infection (CDI) is a serious problem within the healthcare environment where the bacterium causes symptoms ranging from mild diarrhoea to life-threatening colitis. In addition to its principal virulent factors, Toxin A and Toxin B, some C. difficile strains produce a binary toxin (CDT) composed of two subunits namely CDTa and CDTb that are produced and secreted from the cell as two separate polypeptides. Once in the gut, these fragments have the potential to combine to form a potent cytotoxin whose role in the pathogenesis of CDI is presently unclear. This thesis is a step towards understanding structural and functional aspects of the binary toxin produced by C. difficile. The first half of this thesis (chapter I and II) provides a brief introduction to the method of structure determination of proteins molecules, i. e. X-ray crystallography and a detailed overview of C. difficile and the three known toxins from C. difficile namely – Toxin A, Toxin B and the binary toxin. Chapter II further focuses on C. difficile binary toxin and other related toxins. These toxins, known as the ADP-ribosylating toxins (ADPRTs) form a big family of potent toxins which includes Cholera, Pertussis and Diphtheria toxins and are capable of transferring the ADP-ribose part of NAD/NADPH to a varity of substrates in the target cell which ultimately results in cell death. The second half of the thesis comprises of experimental procedures that were carried out during the course of this study and their results. Cloning and expression methods for recombinant CDTa and CDTb in bacterial system followed by their purification are described with the abnormal behaviour exhibited by CDTb (chapter III). We show for the first time that purified CDTa and CDTb can combine to form an active CDT which is cytotoxic to Vero cells (Chapter IV). The purification processes described yielded milligram quantities of binary toxin fragments of high purity that led to the successful crystallisation of the proteins (chapter IV) for further functional and structural studies. High resolution crystal structures of CDTa in its native form (at pH 4.0, 8.5 and 9.0) and in complex with the ADP ribose donors -NAD and NADPH (at pH 9.0) have been determined (chapter V). The crystal structures of the native protein show ‘pronounced conformational flexibility’ confined to the active site region of the protein and ‘enhanced’ disorder at low pH while the complex structures highlight significant differences in ‘ligand specificity’ compared with the enzymatic subunit of a close homologue, Clostridium perfringens Iota toxin (Ia). These structural data provide the first detailed information on protein-donor substrate complex stabilisation in CDTa which may have implications in understanding CDT recognition. Crystallisation of CDTb yielded preliminary crystals. The optimisation of these crystallisation conditions is underway. The thesis concludes with some thoughts and discussion on future directions of this research.
A process for selection and implementation of conservation approaches

In this book, we have described a variety of approaches designed to achieve biological conservation objectives for both rare and little-known species. Resource managers are usually most concerned, for practical reasons, with approaches that conserve large-bodied and better-known taxa. Because we know so little about population status and life history requirements of rare or little-known (RLK) species, conservation managers have been forced to assume that the needs of these species are being met via proxy through our management of vegetation communities and well-studied species. Because so much of the world's biological diversity consists of rarer and more poorly known species (see chaps. 3 and 4), our focus on these species is warranted. In this chapter, we propose a process by which a land manager might evaluate the conservation issues on a particular planning area and select a set of approaches to address those issues.
The Role of e-readiness Assessment Criteria in Accepting e-commerce for Small and Medium Size enterprises-Development of Technology Acceptance Model

This paper develops Davis technology acceptance model by adding two criteria of e-readiness assessment. For small and medium size enterprises, the paper evaluates the credit of developed model in studying the efficient factors in internet technology acceptance, which is one of the most applicable communication tools in e-commerce. The added factors, taken from models and means of e-readiness assessment, are ”existing information technology infrastructures” as well as ”organization's training”. The authors study 45 small and medium size enterprises in the city of Tehran, which are active in information technology products and services. Using Lisrel structural equation modelling, it is shown that there is a meaningful relationship between the added factors and the variables indicating internet network usage. Therefore, the better factors of e-readiness assessment lead to the higher acceptance level of electronic communication tools in e-commerce.
Subglandular mammary augmentation with aqua dissection

Background: The traditional transaxillary approach of submuscular implant breast augmentation is accompanied by severe pain, heavy bleeding, and many side effects. This subglandular mammary augmentation with aqua dissection (SMAAD) is developed for cover above problems. Objective: Surgery with little bleeding is characterized by mild pain, minor side effects, and a short operating time. Methods: The main accomplishment of sub-glandular mammary augmentation accompanied by aqua dissection and the finger dissection without use of instruments through a half incision of the subareolar area pre-treated by the Klein solution (Aqua-dissection), which is the main technique used to minimize bleeding. An injection of 250 ml of Klein solution was inserted in each breast before incision and the finger-only technique was used for pocket dissection. A 200 to 350 ml textured cohesive gel implant was inserted. The drain-keep time was 2 to 7 days. Results: Among the 600 operational patients, only 7 cases underwent capsular contracture and 4 cases experienced hematoma. An average operation time was short (about 40 minutes). This caused by short pocket dissection help of aqua dissection. The merits of SMAAD are numerous (a low rate of capsular contraction and short time operation and normal life was possible just after operation), which indicates why it could be said that an epochal method of implant breast augmentation. Conclusion: This study was performed to evaluate the results of 600 cases of SMAAD. And indicates why SMAAD is a simple, less painful, and less side-effect-inducing surgical technique.
Neurogenesis and its Association to Epileptogenesis in Temporal Lobe Epilepsy

------------------------------------------------------------------------Abstract Temporal lobe epilepsy (TLE) is the most common partial epilepsy 11 . Therefore, it is crucial to understand the mechanisms that contribute to the development of chronic TLE. It was generally believed that neurogenesis took place only during brain development, until in recent years proliferating cells were identified in the hippocampal dentate gyrus and olfactory bulb, providing compelling evidence that neurogenesis still occurs during adult life. Interestingly, studies have shown that seizure activity affects cell proliferation in animal models, proposing that it may potentially be involved in epileptogenesis. As yet, several studies have addressed this issue, yielding contradicting results. It has been demonstrated in animal seizure models that during the acute phase, neurogenesis briefly increases, subsequently decreasing in the chronic phase. Accumulating evidence suggests that neurogenesis does not play an essential role in epileptogenesis in adult rodents. Interestingly, age and/or disease related changes have been implicated in modifying the hippocampal environment so it no longer supports or promotes neurogenesis. Further, studies have shown that status epilepticus induction elicits a different response in the immature hippocampus, implying that in pups aberrant neurogenesis may play a more important role in epileptogenesis. Therefore, it should be determined whether neurogenesis is aberrant following seizures in rat pups and if it has long-term effects on the development of chronic seizures.
Clusterin/Apo J protein expression in plasma samples of an elderly Sardinian population

Clusterin (CLU) is a glycoprotein with a nearly ubiquitous tissue distribution that has been reported to be implicated in several physiological processes as well as in many pathological conditions including ageing, diabetes, atherosclerosis, degenerative diseases and tumorigenesis. In this work we studied the changes in the CLU protein expression in plasma samples of a Sardinian population divided by age into four groups. We applied a proteomic approach using 2D-PAGE-MS analyses, western immunoblotting and ELISA to perform comparisons between the four groups. The typical train of spots of the Clusterin protein in a 2D plasma map was examined and according to statistical analyses five spots were detected as being differentially expressed within the four groups. Regarding total Clusterin the results agree with the data shown by literature but only values up to 90 years old have been reported for Clusterin protein expression. This work extends to older people showing that after 90 a decrease in plasma Clusterin levels seems to occur especially in centenarians. Considering that Clusterin is a sensitive biosensor of oxidative stress it could be in accordance with the fact that centenarians, considered as a model of successful ageing, are characterized by low levels of ROS (radical oxygen species).
A Digital RF Transmitter With Background Nonlinearity Correction

This article describes a new digital transmitter architecture that automatically corrects static and dynamic nonlinearities with no need for digital predistortion or adaptation. We draw upon the Newton–Raphson method of solving equations and show that it leads to <inline-formula> <tex-math notation="LaTeX">$\Delta \Sigma $ </tex-math></inline-formula> modulation as a special case and to a compact, efficient transmitter in the general case. A complete transmitter realized in 28-nm CMOS technology achieves an overall efficiency of 50% while delivering +24 dBm with an adjacent channel power ratio of −35.4 dB and a receive-band noise of −150 dBc/Hz.
The Human Microbiome and Gender Medicine

Discoveries in molecular genetics over the last two decades have broadened our information about the genomics of complex microbial communities. As in all other fields of medicine, there is an undeniable need to explore the microbiome and the way it is impacted by biological sex. A number, although small, of recent studies have demonstrated that women and men have striking differences in the species that constitute their microbiomes. This effects pathological physiology in fields such as hepatology, oncology, autoimmune disease (most notably diabetes mellitus), autism, and obstetrics. There is still an unfortunate lack of research being done on the “microgenderome”: the interaction between microbiota, sex hormones, and the immune system. This review will highlight some of the main areas to be affected by microgenderome physiology, with an in depth focus on obstetrics.
The Challenges Involved in Establishing a Research Technique

Many research techniques are well-accepted within the Information Systems (IS) discipline. From time to time, however, a researcher investigates a question that requires a novel approach. It is then incumbent on the researcher to justify that approach. The IS discipline has accumulated a large corpus of published works. A project is being undertaken whose purpose is to establish the conceptual foundations for a research technique for the critical analysis of published works, and to develop methodological guidance for its application. This article discusses the challenges that have confronted that undertaking.
An Integrated Cell Region Reconstruction Method Based upon Mask R-CNN Model and Improved Voronoi Algorithm

Cell region segmentation in IHC staining images is the basis for quantitative analysis, which is very challenging due to the incomplete membrane staining in IHC images. In this paper, we propose a novel integrated cell region reconstruction method based upon Mask R-CNN model and improved Voronoi algorithm to reconstruct cell region in incomplete IHC staining images, in which Mask R-CNN model is introduced to perform nucleus segmentation, and then the improved Voronoi algorithm with the prior knowledge of nucleus-cytoplasm ratio is used to reconstruct the whole cell region. We also develop a framework for the integrated method to achieve automatic end-to-end cell region segmentation. Our method could better solve the problem of cell segmentation under incomplete staining than only deep-learning method or standard Voronoi algorithm, and the reconstructed cell region could better fit the real cell boundary.