Miracle-dz/UniFAR-FTUs huggingface dataset:
Rainforest Conversion in Central Sulawesi, Indonesia: Recent Development and Consequences for River Discharge and Water Resources: An Integrated Remote Sensing and Hydrological Modelling Approach

Summary: The present land cover of humid tropical catchment areas mainly regulates the flow of vapour to the atmosphere.Therefore land use decisions play an important role for the water balance of a tropical catchment. Studies that relate land coverchanges with river discharge changes for humid tropical catchment areas at the mesoscale level are rare. This article applies anintegrated remote sensing and hydrological modelling approach to analyse the impact of land cover changes on the water resources of a mesoscale humid tropical catchment. First, a change detection analysis of Landsat/ ETM + satellite images wascarried out to quantify land cover changes of the mesoscale Gumbasa River catchment in Central Sulawesi, Indonesia. There-after the distributed hydrological model WASIM-ETH was calibrated and validated for the current Landsat/ ETM + scene.The historical Landsat/ ETM + scene was integrated for the hydrological model application as a historical land cover scenario.Further hypothetical total-change scenarios were carried out. The results of the hydrological model scenario application clearlydemonstrate a strong relationship between deforestation rates and increasing discharge variability. Especially a significant increase of high water discharges was simulated for the applied scenarios. With regard to the high deforestation rates of the research catchment, one can expect further changes of the water balance.
Huntingtin-associated Protein 1 (HAP1) Is a cGMP-dependent Kinase Anchoring Protein (GKAP) Specific for the cGMP-dependent Protein Kinase Iβ Isoform*

Background: Protein kinase compartmentalization through anchoring proteins provides spatiotemporal specificity. Results: Competitive elution combined with cyclic nucleotide affinity enrichment identifies HAP1 as a putative novel PKG anchoring protein (GKAP). Conclusion: Secondary structure predictions, in vitro binding studies, and site-directed mutagenesis define the binding domain and classify HAP1 as a GKAP specifically anchoring PKG Iβ. Significance: The repertoire of PKG anchoring proteins is expanded, enforcing that also PKG signaling is tightly spatiotemporally regulated. Protein-protein interactions are important in providing compartmentalization and specificity in cellular signal transduction. Many studies have hallmarked the well designed compartmentalization of the cAMP-dependent protein kinase (PKA) through its anchoring proteins. Much less data are available on the compartmentalization of its closest homolog, cGMP-dependent protein kinase (PKG), via its own PKG anchoring proteins (GKAPs). For the enrichment, screening, and discovery of (novel) PKA anchoring proteins, a plethora of methodologies is available, including our previously described chemical proteomics approach based on immobilized cAMP or cGMP. Although this method was demonstrated to be effective, each immobilized cyclic nucleotide did not discriminate in the enrichment for either PKA or PKG and their secondary interactors. Hence, with PKG signaling components being less abundant in most tissues, it turned out to be challenging to enrich and identify GKAPs. Here we extend this cAMP-based chemical proteomics approach using competitive concentrations of free cyclic nucleotides to isolate each kinase and its secondary interactors. Using this approach, we identified Huntingtin-associated protein 1 (HAP1) as a putative novel GKAP. Through sequence alignment with known GKAPs and secondary structure prediction analysis, we defined a small sequence domain mediating the interaction with PKG Iβ but not PKG Iα. In vitro binding studies and site-directed mutagenesis further confirmed the specificity and affinity of HAP1 binding to the PKG Iβ N terminus. These data fully support that HAP1 is a GKAP, anchoring specifically to the cGMP-dependent protein kinase isoform Iβ, and provide further evidence that also PKG spatiotemporal signaling is largely controlled by anchoring proteins.
Femoral artery pressure monitoring

A case of bilateral femoral arterial occlusion following the Seldinger technique of arterial puncture for monitoring blood pressure is described. Sixty patients were closely studied for possible complications of this technique, using pedal blood pressure, and skin temperature to supplement clinical observation. Despite the occasional complications which are described we consider this to be a safe and valuable technique in selected circumstances.
Does Extra Interletter Spacing Help Text Reading in Skilled Adult Readers?

Abstract A number of experiments have shown that, in skilled adult readers, a small increase in interletter spacing speeds up the process of visual word recognition relative to the default settings (i.e., judge faster than judge). The goal of the present experiment was to examine whether this effect can be generalized to a more ecological scenario: text reading. Each participant read two stories (367 words each) taken from a standardized reading test. The stories were presented with the standard interletter spacing or with a small increase in interletter spacing (+1.2 points to default) in a within-subject design. An eyetracker was used to register the participants’ eye movements. Comprehension scores were also examined. Results showed that, on average, fixation durations were shorter while reading the text with extra spacing than while reading the text with the default settings (237 vs. 245 ms, respectively; η2 =. 41, p = .01). However, the number of fixations (while nonsignificant) was slightly higher in the text with extra spacing than in the text with the default spacing, and cancelled out the effect of interletter spacing in total reading times (F < 1). Comprehension scores were similar in the two spacing conditions (F < 1). Thus, at least for skilled adult readers, interletter spacing does not seem to play a consistently facilitative role during text reading.
Proteomics in Animal Health and Production

Proteomics is a powerful tool for the identification of proteins and study their localisation, functions, modifications and possible interactions or complexes they can form. This review presents an overview of proteome studies of various tissues and biological fluids in different farm animals. Proteomics is the key tool to understand the molecular mechanisms behind meat quality in different genetic back grounds or processing technologies. Several studies carried out on the liver proteome of many species either to mapping the proteins or for comparing them in various conditions. The difference in the proteome of tears in various animal species could explain their adaptation to their climatic conditions. Saliva with its hundreds of proteins, peptides, hormones, electrolytes and other chemical compounds might be a good source of biomarkers which helps in assessing stress factors such as malnutrition as well as diseases or ongoing viral infections in farm animals. Saliva proteome of ruminants could be differentiated from non- ruminants. Proteins are key molecules of the milk functional component repertoire and their investigation reveals differential expression in various animals. The study of proteome can provide a deeper understanding of the biochemical, physiological aspects of farm animal biology and it's relation to productive aspects and disease conditions.
Concurrent sequence analysis of 5' and 3' RNA termini by intramolecular circularization reveals 5' nontemplated bases and 3' terminal heterogeneity for lymphocytic choriomeningitis virus mRNAs

We have used a technique of RNA circularization coupled with polymerase chain reaction amplification for simultaneous analysis of the 5' and 3' termini of subgenomic mRNAs derived from the S RNA of lymphocytic choriomeningitis virus during an acute infection of BHK cells. These mRNAs possess 1 to 7 nontemplated nucleotides of apparently random sequence at their 5' ends. The predominant mRNA species have 4 or 5 nontemplated nucleotides. The 5' termini of the mRNAs also have properties consistent with the presence of a 5' cap structure. The 3' termini of the mRNAs lack poly(A) tails, and we have shown that transcription termination occurs at heterogeneous positions within the intergenic region of the S RNA. The identification of several distinct termini in the vicinity of a putative stem-loop structure in the RNA templates suggests that transcription termination may be mediated by a structural signal rather than a precise sequence signal.
Optimizing IP Flow Classification Using Feature Selection

The identification of network applications is essential to numerous network activities. Unfortunately, traditional port-based classification and packet payload-based analysis exhibit a number of shortfalls. An alternative is to use Machine Learning (ML) techniques and identify network applications based on per-flow features. Since a lot of flow features can be used for flow classification and there are many irrelevant and redundant features among them, feature selection plays a vital role in performance optimizing. In this paper, we propose a wrapper-based feature selection method for IP flow classification using modified random-mutation hill-climbing (RMHC) and C4.5 algorithm (MRMHC-C4.5). The experiments show our approach can greatly improve computational performance without negative impact on classification accuracy.
A Multi-stage Method to Extract Road from High Resolution Satellite Image

Extracting road information from high-resolution satellite images is complex and hardly achieves by exploiting only one or two modules. This paper presents a multi-stage method, consisting of automatic information extraction and semi-automatic post-processing. The Multi-scale Enhancement algorithm enlarges the contrast of human-made structures with the background. The Statistical Region Merging segments images into regions, whose skeletons are extracted and pruned according to geometry shape information. Setting the start and the end skeleton points, the shortest skeleton path is constructed as a road centre line. The Bidirectional Adaptive Smoothing technique smoothens the road centre line and adjusts it to right position. With the smoothed line and its average width, a Buffer algorithm reconstructs the road region easily. Seen from the last results, the proposed method eliminates redundant non-road regions, repairs incomplete occlusions, jumps over complete occlusions, and reserves accurate road centre lines and neat road regions. During the whole process, only a few interactions are needed.
Effects of repetitive transcranial magnetic stimulation in performing eye–hand integration tasks: Four preliminary studies with children showing low-functioning autism

This report, based on four studies with children with low-functioning autism, aimed at evaluating the effects of repetitive transcranial magnetic stimulation delivered on the left and right premotor cortices on eye–hand integration tasks; defining the long-lasting effects of high-frequency repetitive transcranial magnetic stimulation; and investigating the real efficacy of high-frequency repetitive transcranial magnetic stimulation by comparing three kinds of treatments (high-frequency repetitive transcranial magnetic stimulation, a traditional eye–hand integration training, and both treatments combined). Results showed a significant increase in eye–hand performances only when high-frequency repetitive transcranial magnetic stimulation was delivered on the left premotor cortex; a persistent improvement up to 1 h after the end of the stimulation; better outcomes in the treatment combining high-frequency repetitive transcranial magnetic stimulation and eye–hand integration training. Based on these preliminary findings, further evaluations on the usefulness of high-frequency repetitive transcranial magnetic stimulation in rehabilitation of children with autism are strongly recommended.
Cisplatin and Oxaliplatin, but Not Carboplatin and Nedaplatin, Are Substrates for Human Organic Cation Transporters (SLC22A1–3 and Multidrug and Toxin Extrusion Family)

We have examined the role of the human organic cation transporters [hOCTs and human novel organic cation transporter (hOCTN); SLC22A1–5] and apical multidrug and toxin extrusion (hMATE) in the cellular accumulation and cytotoxicity of platinum agents using the human embryonic kidney (HEK) 293 cells transiently transfected with the transporter cDNAs. Both the cytotoxicity and accumulation of cisplatin were enhanced by the expression of hOCT2 and weakly by hOCT1, and those of oxaliplatin were also enhanced by the expression of hOCT2 and weakly by hOCT3. The hOCT-mediated uptake of tetraethylammonium (TEA) was markedly decreased in the presence of cisplatin in a concentration-dependent manner. However, oxaliplatin showed almost no influence on the TEA uptakes in the HEK293 cells expressing hOCT1, hOCT2, and hOCT3. The hMATE1 and hMATE2-K, but not hOCTN1 and OCTN2, mediated the cellular accumulation of cisplatin and oxaliplatin without a marked release of lactate dehydrogenase. Oxaliplatin, but not cisplatin, markedly decreased the hMATE2-K-mediated TEA uptake. However, the inhibitory effect of cisplatin and oxaliplatin against the hMATE1-mediated TEA uptake was similar. The release of lactate dehydrogenase and the cellular accumulation of carboplatin and nedaplatin were not found in the HEK293 cells transiently expressing these seven organic cation transporters. These results indicate that cisplatin is a relatively good substrate of hOCT1, hOCT2, and hMATE1, and oxaliplatin is of hOCT2, hOCT3, hMATE1, and hMATE2-K. These transporters could play predominant roles in the tissue distribution and anticancer effects and/or adverse effects of platinum agent-based chemotherapy.
A computational framework for implementing agent consciousness.

Mainly relying on Baars’ "Global Workspace" theory of consciousness, we identify computational correlates of consciousness and discuss their possible representation within a model of intelligent agents. We first review a particular agent implementation that is given by an abstract machine, and then identify the extensions that are required in order to accommodate the main aspects of consciousness. This amounts to unconscious process coalitions that result in the creation of contexts. These extensions can be formulated within a reified virtual machine encompassing a representation of the original machine as well as an additional introspective component. This computational framework is illustrating throughout using a simple working example.
Electrostimulation to reduce synaptic scaling driven progression of Alzheimer's disease

Cell death and synapse dysfunction are two likely causes of cognitive decline in AD. As cells die and synapses lose their drive, remaining cells suffer an initial decrease in activity. Neuronal homeostatic synaptic scaling then provides a feedback mechanism to restore activity. This homeostatic mechanism is believed to sense levels of activity-dependent cytosolic calcium within the cell and to adjust neuronal firing activity by increasing the density of AMPA synapses at remaining synapses to achieve balance. The scaling mechanism increases the firing rates of remaining cells in the network to compensate for decreases in network activity. However, this effect can itself become a pathology, as it produces increased imbalance between excitatory and inhibitory circuits, leading to greater susceptibility to further cell loss via calcium-mediated excitotoxicity. Here, we present a mechanistic explanation of how directed brain stimulation might be expected to slow AD progression based on computational simulations in a 470-neuron biomimetic model of a neocortical column. The simulations demonstrate that the addition of low-intensity electrostimulation (neuroprosthesis) to a network undergoing AD-like cell death can raise global activity and break this homeostatic-excitotoxic cascade. The increase in activity within the remaining cells in the column results in lower scaling-driven AMPAR upregulation, reduced imbalances in excitatory and inhibitory circuits, and lower susceptibility to ongoing damage.
Multi‐transfer: Transfer learning with multiple views and multiple sources

Transfer learning, which aims to help learning tasks in a target domain by leveraging knowledge from auxiliary domains, has been demonstrated to be effective in different applications such as text mining, sentiment analysis, and so on. In addition, in many real‐world applications, auxiliary data are described from multiple perspectives and usually carried by multiple sources. For example, to help classify videos on Youtube, which include three perspectives: image, voice and subtitles, one may borrow data from Flickr, Last.FM and Google News. Although any single instance in these domains can only cover a part of the views available on Youtube, the piece of information carried by them may compensate one another. If we can exploit these auxiliary domains in a collective manner, and transfer the knowledge to the target domain, we can improve the target model building from multiple perspectives. In this article, we consider this transfer learning problem as Transfer Learning with Multiple Views and Multiple Sources. As different sources may have different probability distributions and different views may compensate or be inconsistent with each other, merging all data in a simplistic manner will not give an optimal result. Thus, we propose a novel algorithm to leverage knowledge from different views and sources collaboratively, by letting different views from different sources complement each other through a co‐training style framework, at the same time, it revises the distribution differences in different domains. We conduct empirical studies on several real‐world datasets to show that the proposed approach can improve the classification accuracy by up to 8% against different kinds of state‐of‐the‐art baselines.
A Comprehensive Biophysical Model of Ion and Water Transport in Plant Roots. I. Clarifying the Roles of Endodermal Barriers in the Salt Stress Response

In this paper, we present a detailed and comprehensive mathematical model of active and passive ion and water transport in plant roots. Two key features are the explicit consideration of the separate, but interconnected, apoplastic, and symplastic transport pathways for ions and water, and the inclusion of both active and passive ion transport mechanisms. The model is used to investigate the respective roles of the endodermal Casparian strip and suberin lamellae in the salt stress response of plant roots. While it is thought that these barriers influence different transport pathways, it has proven difficult to distinguish their separate functions experimentally. In particular, the specific role of the suberin lamellae has been unclear. A key finding based on our simulations was that the Casparian strip is essential in preventing excessive uptake of Na+ into the plant via apoplastic bypass, with a barrier efficiency that is reflected by a sharp gradient in the steady-state radial distribution of apoplastic Na+ across the barrier. Even more significantly, this function cannot be replaced by the action of membrane transporters. The simulations also demonstrated that the positive effect of the Casparian strip of controlling Na+ uptake, was somewhat offset by its contribution to the osmotic stress component: a more effective barrier increased the detrimental osmotic stress effect. In contrast, the suberin lamellae were found to play a relatively minor, even non-essential, role in the overall response to salt stress, with the presence of the suberin lamellae resulting in only a slight reduction in Na+ uptake. However, perhaps more significantly, the simulations identified a possible role of suberin lamellae in reducing plant energy requirements by acting as a physical barrier to preventing the passive leakage of Na+ into endodermal cells. The model results suggest that more and particular experimental attention should be paid to the properties of the Casparian strip when assessing the salt tolerance of different plant varieties and species. Indeed, the Casparian strip appears to be a more promising target for plant breeding and plant genetic engineering efforts than the suberin lamellae for the goal of improving salt tolerance.
Review of the Brazilian Atlantic Rainforest harvestman Longiperna (Opiliones: Gonyleptidae: Mitobatinae)

Longiperna Roewer, 1929 is revised and new records of distribution are presented for the Brazilian Costal Atlantic Rain Forest (from Rio de Janeiro to Santa Catarina states). The following new synonymies are established: Longiperna concolor (Mello-Leitao, 1923) = L. zonata Mello-Leitao, 1935 and L. heliaca B. Soares, 1942; Longiperna coxalis (Roewer, 1943) = L. areolata B. Soares, 1944; Longiperna insperata (Soares & Soares, 1947) = L. paranensis Soares & Soares, 1947 and L. curitibana Kury, 2003. Two new species are described: Longiperna kuryi sp. nov. (type-locality: Brazil, Rio de Janeiro, Parati); Longiperna trembao sp. nov. (type-locality: Brazil, Minas Gerais, Belo Horizonte).
External load training does not alter balance performance in well-trained women

Abstract This study investigated the influence of external load training (ELT) on static and dynamic balance. Nineteen females stratified into two groups (ELT = 9, control = 10) completed three testing sessions over 6 weeks. The ELT group wore weighted vests (WV) of ~8% body mass for 32 h/week during daily living and three training sessions/week for 3 weeks. Following completion of ELT, a 3 week detraining (DET) phase was completed. Bilateral and unilateral static balance were assessed with eyes open and closed. Dynamic balance was assessed using the star excursion balance test (SEBT). Static and dynamic balance variables were analysed using a 2 (group) x 3 (time) between participants repeated measures ANOVA (p < 0.05). Results revealed significant reductions in average centre of pressure (COP) velocity in the control group on the non-dominant limb with eyes closed, and significantly greater reach distances in the ELT group on the SEBT for the posteromedial and medial directions on the dominant limb (p < 0.05). These findings suggest the ELT group did not significantly improve their balance in comparison to the control group. However, future research should further examine this unique, supplemental training method and the impact on balance performance.
A Language-Independent Neural Network-Based Speech Synthesizer

The applicability of soft computing to implementing text-to-speech conversion is subject to debate. Using neural networks for phoneme-level, text-to-speech conversion has several advantages over hard computing. Soft computing’s capacity to generalize makes it possible to map words missing from the database, as well as to reduce contradictions related to different pronunciations for the same word. Neural networks have been shown to optimally solve a large class of applied pattern-matching problems, but very little research has been done to match the requirements of pattern generation in machine-to-human interaction. An artificial speech synthesizer based on neural networks is being developed for application to deeply embedded systems for language-independent speech commands on hands-free interfaces. A feed-forward, backpropagation artificial neural network has been trained for this purpose using a custom-developed, regular expression-based, text-to-phones transcription engine to generate training patterns. Initial experimental results show the expected properties of language independence and in-system learning.