Miracle-dz/UniFAR-FTUs huggingface dataset:
Determinants of Paddy Fields Conversion in Java Island, Indonesia

Rice is a main staple food of Indonesia. Availability of rice is not separated from Java island as the largest rice supplier in Indonesia. Almost 52% of Indonesia's rice production is produced on the Java island. However, production growth is only 0,7% given the increasing number of people. One of the causes is the increasing land conversion over the past 7 years. This study aims to 1) to identify how much land conversion in Java island from 1994 to 2014, 2) to analyze what factors affect the conversion of paddy fields in Java island, and 3) to calculate the impact of paddy field conversion on paddy production and economic value of farmer job for 21 years in Java island. The results indicate that during the period of 1994 to 2014, Java island experienced a conversion of rice fields of 1.2 million hectares or about 60 thousand hectares per year. Productivity of paddy rice, economic growth (GRDP), length of asphalt road, and population growth have significant effect on the conversion of paddy fields in Java island. For 21 years, Java island has lost the opportunity to produce rice by 6.7 million tons with a value of Rp 24,282 trillion rupiah.
Distance-Based Functional Diversity Measures and Their Decomposition: A Framework Based on Hill Numbers

Hill numbers (or the “effective number of species”) are increasingly used to characterize species diversity of an assemblage. This work extends Hill numbers to incorporate species pairwise functional distances calculated from species traits. We derive a parametric class of functional Hill numbers, which quantify “the effective number of equally abundant and (functionally) equally distinct species” in an assemblage. We also propose a class of mean functional diversity (per species), which quantifies the effective sum of functional distances between a fixed species to all other species. The product of the functional Hill number and the mean functional diversity thus quantifies the (total) functional diversity, i.e., the effective total distance between species of the assemblage. The three measures (functional Hill numbers, mean functional diversity and total functional diversity) quantify different aspects of species trait space, and all are based on species abundance and species pairwise functional distances. When all species are equally distinct, our functional Hill numbers reduce to ordinary Hill numbers. When species abundances are not considered or species are equally abundant, our total functional diversity reduces to the sum of all pairwise distances between species of an assemblage. The functional Hill numbers and the mean functional diversity both satisfy a replication principle, implying the total functional diversity satisfies a quadratic replication principle. When there are multiple assemblages defined by the investigator, each of the three measures of the pooled assemblage (gamma) can be multiplicatively decomposed into alpha and beta components, and the two components are independent. The resulting beta component measures pure functional differentiation among assemblages and can be further transformed to obtain several classes of normalized functional similarity (or differentiation) measures, including N-assemblage functional generalizations of the classic Jaccard, Sørensen, Horn and Morisita-Horn similarity indices. The proposed measures are applied to artificial and real data for illustration.
Whole-Exome Sequencing Reveals Defective CYP3A4 Variants Predictive of Paclitaxel Dose-Limiting Neuropathy

Purpose: Paclitaxel, a widely used chemotherapeutic drug, can cause peripheral neuropathies leading to dose reductions and treatment suspensions and decreasing the quality of life of patients. It has been suggested that genetic variants altering paclitaxel pharmacokinetics increase neuropathy risk, but the major causes of interindividual differences in susceptibility to paclitaxel toxicity remain unexplained. We carried out a whole-exome sequencing (WES) study to identify genetic susceptibility variants associated with paclitaxel neuropathy. Experimental Design: Blood samples from 8 patients with severe paclitaxel-induced peripheral neuropathy were selected for WES. An independent cohort of 228 cancer patients with complete paclitaxel neuropathy data was used for variant screening by DHPLC and association analysis. HEK293 cells were used for heterologous expression and characterization of two novel CYP3A4 enzymes. Results: WES revealed 2 patients with rare CYP3A4 variants, a premature stop codon (CYP3A4*20 allele) and a novel missense variant (CYP3A4*25, p.P389S) causing reduced enzyme expression. Screening for CYP3A4 variants in the independent cohort revealed three additional CYP3A4*20 carriers, and two patients with missense variants exhibiting diminished enzyme activity (CYP3A4*8 and the novel CYP3A4*27 allele, p.L475V). Relative to CYP3A4 wild-type patients, those carrying CYP3A4 defective variants had more severe neuropathy (2- and 1.3-fold higher risk of neuropathy for loss-of-function and missense variants, respectively, P = 0.045) and higher probability of neuropathy-induced paclitaxel treatment modifications (7- and 3-fold higher risk for loss-of-function and missense variants, respectively, P = 5.9 × 10−5). Conclusion: This is the first description of a genetic marker associated with paclitaxel treatment modifications caused by neuropathy. CYP3A4 defective variants may provide a basis for paclitaxel treatment individualization. Clin Cancer Res; 21(2); 322–8. ©2014 AACR.
The SABAP2 "Four Degrees Blue" project: the challenge to obtain at least 11 checklists in 576 pentads

The Four Degrees Blue challenge was launched on 22 August 2015. At this stage 201 checklists were needed from 111 pentads; the northwest degree cell needed the most checklists, 109, and the southeast degree cell needed only 11. The aim was to have all remaining dark green pentads on the Gauteng coverage map turn to blue with 11 atlas checklists . the last remaining pentads turned blue on 29 June 2016.
Peri-implant diseases: diagnosis and risk indicators.

BACKGROUND Peri-implant diseases include peri-implant mucositis, describing an inflammatory lesion of the peri-implant mucosa, and peri-implantitis, which also includes loss of supporting bone. METHODS A literature search of the Medline database (Ovid), up to 21 January 2008 was carried out using a systematic approach, in order to review the evidence for diagnosis and the risk indicators for peri-implant diseases. RESULTS Experimental and clinical studies have identified various diagnostic criteria including probing parameters, radiographic assessment and peri-implant crevicular fluid and saliva analyses. Cross-sectional analyses have investigated potential risk indicators for peri-implant disease including poor oral hygiene, smoking, history of periodontitis, diabetes, genetic traits, alcohol consumption and implant surface. There is evidence that probing using a light force (0.25 N) does not damage the peri-implant tissues and that bleeding on probing (BOP) indicates presence of inflammation in the peri-implant mucosa. The probing depth, the presence of BOP, and suppuration should be assessed regularly for the diagnosis of peri-implant diseases. Radiographs are required to evaluate supporting bone levels around implants. The review identified strong evidence that poor oral hygiene, a history of periodontitis and cigarette smoking, are risk indicators for peri-implant disease. Future prospective studies are required to confirm these factors as true risk factors.
Enterovirus 71 Infection of Monocytes with Antibody-Dependent Enhancement

ABSTRACT Enterovirus (EV) is an RNA virus that has circulated with different serotypes and genotypes worldwide. Enterovirus 71 (EV71) is a major neurotropic virus that causes severe brain stem encephalitis (BE) in infants and young children. The most vulnerable age for fatal infection is 6 to 11 months. This is associated with the coincident decline in maternal antibodies. The current report describes our finding that EV71 can infect human peripheral blood monocytes. We were able to show that EV71 infection is enhanced in the monocytic cell line THP-1 by the presence of subneutralizing concentrations of anti-EV71 antibodies. We also found that antibody-dependent enhancement (ADE) is mediated in part by Fcγ receptors. These observations support the concept that ADE augments the infectivity of EV71 for human monocytes and contributes to the age-dependent pathogenesis of EV71-induced disease. The ADE phenomenon must be considered during the development of an EV71 vaccine.
Assessment of clot length with multiphase CT angiography in patients with acute ischemic stroke

Introduction Existing stroke literature demonstrates that rapid recanalization of vessels improves long-term prognosis after acute ischemic stroke. However, further optimization of the speed of the thrombectomy procedure, used to recanalize a blocked vessel, is limited by our minimal knowledge of the clot dimensions pre-procedure. Knowing the clot dimensions would allow planning of the thrombectomy procedure with the appropriate size and length of stent retriever, and determination of the correct site of the stent deployment ensuring total coverage of the clot by the stent retriever. Methods We performed a feasibility study to assess if multiphase computed tomography angiography (mCTA) can be used to estimate clot length by comparing CTA imaging data with imaging data obtained from conventional digital subtraction angiography (DSA). A retrospective chart review was performed of patients with clots in the proximal middle cerebral artery and adequate collateral circulation, who underwent both mCTA and DSA. Results Clot length was not significantly different on 3D mCTA versus mCTA MIPs, nor was it significantly different on MIP mCTA versus DSA. Pathological evidence also supported our ability to measure clot length on mCTA. Conclusions We suggest that mCTA is a reliable and valid measure of clot length in acute ischemic stroke patients.
Yeast apurinic/apyrimidinic endonuclease Apn1 protects mammalian neuronal cell line from oxidative stress

Reactive oxygen species (ROS) have been implicated as one of the agents responsible for many neurodegenerative diseases. A critical target for ROS is DNA. Most oxidative stress‐induced DNA damage in the nucleus and mitochondria is removed by the base excision repair pathway. Apn1 is a yeast enzyme in this pathway which possesses a wider substrate specificity and greater enzyme activity than its mammalian counterpart for removing DNA damage, making it a good therapeutic candidate. For this study we targeted Apn1 to mitochondria in a neuronal cell line derived from the substantia nigra by using a mitochondrial targeting signal (MTS) in an effort to hasten the removal of DNA damage and thereby protect these cells. We found that following oxidative stress, mitochondrial DNA (mtDNA) was repaired more efficiently in cells containing Apn1 with the MTS than controls. There was no difference in nuclear repair. However, cells that expressed Apn1 without the MTS showed enhanced repair of both nuclear and mtDNA. Both Apn1‐expressing cells were more resistant to cell death following oxidative stress compared with controls. Therefore, these results reveal that the expression of Apn1 in neurons may be of potential therapeutic benefit for treating patients with specific neurodegenerative diseases.
Traffic jam modeling and simulation

In this paper various theories on traffic jams and stop-and-go wave modeling were reviewed and discussed. These include traditional microscopic car-following model, asymmetric traffic theory, first-order and second-order macroscopic models, traffic disturbance model, phase transition model as well as macroscopic simulation. The mechanism of stop-and-go waves, causes, generation, propagation, and absorption was discussed. A macroscopic simulation model was developed which suits for both free flow and stop-and-go traffic conditions. Ten hours of macroscopic simulation was performed on a section of freeway in California. The model predicted traffic speed and density were compared with field measured data. It was concluded that by applying proper boundary conditions for each roadway segment and incorporating capacity drop in the model, the macroscopic simulation model can reasonably predict the stop-and-go traffic states.
Polymorphism in apoA1 Influences High-Density Lipoprotein Cholesterol Levels but Is Not a Major Risk Factor of Alzheimer's Disease

Background: Apolipoprotein A1 (apoA1) is the major apolipoprotein constituent of the high-density lipoprotein (HDL) and is involved in reverse cholesterol transport. Variation in the apoA1 gene might influence the function of the protein and, thus, brain cholesterol metabolism, leading to an increased risk for Alzheimer’s disease (AD). Aim: In the current report, we investigated the role of the functional apoA1 polymorphism (–75 G/A) as a genetic risk factor for AD in a Tunisian population. Methods: 173 AD patients and 150 healthy controls were studied. Results: No association was found between this genetic variation in apoA1 gene and the risk of AD. The presence of the (–75 G/A) A allele appeared, however, to be associated with lower levels of cerebrospinal fluid Aβ42 and HDL cholesterol levels in sera. Conclusion: Our data support the observation that apoA1 polymorphism influences cholesterol metabolism and Aβ42 deposition in the brain.
Word order in wh-questions in a North Norwegian dialect: some evidence from an acquisition study

While standard Norwegian is a V2 language, some Norwegian dialects exhibit V3 in certain types of wh-questions. In some previous work on the Tromsø dialect, V3 has been considered the ‘true’ dialect and speakers' acceptance of V2 simply a result of the influence from the standard language. Based on child and adult data from a study of the acquisition of word order in the Tromsø dialect, I will argue that both V2 and V3 orders are part of the dialect – used by adult speakers and acquired (more or less) simultaneously by children. It will further be argued that the choice between the two depends on the information structure of the sentence, more specifically, on the interpretation of the subject as given or new information.
Speaker adaptation of convolutional neural network using speaker specific subspace vectors of SGMM

The recent success of convolutional neural network (CNN) in speech recognition is due to its ability to capture translational variance in spectral features while performing discrimination. The CNN architecture requires correlated features as input and thus fMLLR transform which is estimated in de-correlated feature space fails to give signiﬁcant improvement. In this paper, we propose two methods for extracting speaker adapted features in a correlated space using SGMMs. First, we estimate fMLLR transforms for correlated features by full covariance Gaussians using SGMM approach. Second, we augment speaker speciﬁc subspace vectors with acoustic features to provide speaker information in CNN models. Finally we propose a bottleneck - joint CNN/DNN framework to exploit the effects of both (fM-LLR+ivectors) and (SGMM-fMLLR+speaker vectors) features. Experiments on TIMIT task show that our proposed features give 5.7 % relative improvement over the log-mel features. Furthermore experiments on switchboard task show that the bottleneck - joint CNN/DNN model achieves 12.2 % relative improvement over baseline joint CNN/DNN framework.
Ontological modeling of motivational messages for physical activity coaching

Smart coaching systems are named to play a central role in both prevention and intervention strategies for behavioral change. While relevant progresses have been made in terms of automatic and continuous monitoring of behavioral aspects, e.g. amount and variety of physical activity, coaching and feedback techniques are still in an infancy stage. Current smart coaching strategies are mostly based on handcrafted messages which hardly personalize to the needs, context and preferences of each user. In order to make these recommendations more realistic, engaging and effective more flexible and sophisticated strategies are needed. This paper presents an ontology-based approach to model personalizable motivational messages for promoting healthy physical activity. The proposed ontology not only models the message intention and its components, e.g. argument, feedback or followup, but also its content, i.e. action, place, time or object required to perform the recommended activity. Through this ontology the messages can also be categorized into multiple classes, e.g. sedentary, mild or vigorous activities, and retrieved based on the preferences, needs and context of the user. Additional information not explicitly present on the messages can be inferred from the ontology by applying reasoning techniques and used to enhance the message retrieval process.
How to build a grid cell

Neurons in the medial entorhinal cortex fire action potentials at regular spatial intervals, creating a striking grid-like pattern of spike rates spanning the whole environment of a navigating animal. This remarkable spatial code may represent a neural map for path integration. Recent advances using patch-clamp recordings from entorhinal cortex neurons in vitro and in vivo have revealed how the microcircuitry in the medial entorhinal cortex may contribute to grid cell firing patterns, and how grid cells may transform synaptic inputs into spike output during firing field crossings. These new findings provide key insights into the ingredients necessary to build a grid cell.
Internet-delivered cognitive behaviour therapy for depression in people with diabetes: study protocol for a randomised controlled trial

Introduction Depression substantially contributes to the personal burden and healthcare costs of living with diabetes mellitus (DM). Comorbid depression and DM are associated with poorer quality of life, poorer self-management and glycemic control, increased risk for DM complications and higher mortality rates, and higher health service utilization. Depression remains under-recognized and undertreated in people with DM, which may, in part, result from barriers associated with accessing face-to-face treatment. This study will examine the efficacy of an internet-based cognitive behaviour therapy programme for major depressive disorder (iCBT-MDD) in people with DM. Methods and analysis A CONSORT 2010 compliant, registered randomised controlled trial of the intervention (iCBT-MDD) versus a treatment as usual control group will be conducted. The study will include 100 adults aged 18 years and over with a diagnosis of type 1 or type 2 DM and self-reported symptoms that satisfy MDD which will enable us to detect a statistically significant difference with a group effect size of 0.6 at a power of 80% and significance level of p=0.05. Participants will be randomised to receive the iCBT-MDD programme immediately, or to wait 10 weeks before accessing the programme. Primary outcomes will be self-reported depression severity, DM-related distress, and glycemic control (glycosylated hemoglobin). Secondary outcomes will be general distress and disability, generalized anxiety, lifestyle behaviours, somatization, eating habits, alcohol use, and acceptability of the iCBT programme to participants, and practicality for clinicians. Data will be analyzed with linear mixed models for each outcome measure. Ethics and dissemination The Human Research Ethics Committee of St Vincent's Hospital Australia have given ethics approval (HREC/13/SVH/291). Results will be disseminated via peer-reviewed publication and social media channels of Australian Diabetes Consumer Representative Bodies. Trial registration number The trial is registered with the Australian and New Zealand Clinical Trials Registry (ACTRN12613001198718).
Functional Neuroimaging and Episodic Memory: A Perspective

One area of research that has significantly benefited from the recent development of functional neuroimaging techniques is the study of memory. In this review we explore what has been learned about the neural basis of normal memory function using these techniques. We focus on episodic memory, which is characterized by the ability to consciously recollect memories for facts or events. We highlight three neuroanatomical regions that have been linked to episodic memory: The hippocampal complex, the prefrontal cortex and the amygdala. For each of these regions, we discuss the behavioral methods of assessment and specific episodic memory processes, particularly encoding and retrieval. Finally, we briefly comment on the potential clinical applications for this research and other memory systems.
A Low Cost Network-on-Chip with Guaranteed Service Well Suited to the GALS Approach

The paper presents the DSPIN micro-network, that is an evolution of the SPIN architecture. DSPIN is a scalable packet switching micro-network dedicated to GALS (globally asynchronous, locally synchronous) clustered, multi-processors, systems on chip. The DSPIN architecture has a very small footprint and provides to the system designer both guaranteed latency, and guaranteed throughput services for real-time applications
Modeling Feedback Bridging Faults with Non-Zero Resistance

We study the behavior of feedback bridging faults with non-zero bridge resistance in both combinational and sequential circuits. We demonstrate that a test vector may detect the fault, not detect the fault or lead to oscillation, depending on bridge resistance. Moreover, the resistance intervals in which a particular behavior is observed are not necessarily contiguous. We demonstrate non-trivial behavior for situations in which a detection seems impossible, namely disabled loops going through a gate with controlling values on its side inputs.We outline the multiple strengths problem which arises due to the fact that a critical bridge resistance depends on the strengths of the signals driving the bridge, which in turn are functions of the number of the on-transistors, these again depending on the bridge resistance, making such a fault very hard to resolve. For sequential circuits, we describe additional difficulties caused by the need to account for implications on bridge behavior, which have originated in the previous time frames. We conclude that the complexity of resistive feedback bridging fault simulation accurate enough to resolve such situations will probably be prohibitively high and propose possible simplifying assumptions. We present simulation results for ISCAS benchmarks using these assumptions with and without taking oscillation into account.
Adaptive voltage over-scaling for resilient applications

We present an energy-reduction strategy for applications which are resilient, i. e. can tolerate occasional errors, based on an adaptive voltage control. The voltage is lowered, possibly beyond the safe-operation region, as long as no errors are observed, and raised again when the severity of the detected errors exceeds a threshold. Due to the resilient nature of the applications, lightweight error detection logic is sufficient for operation, and no expensive error recovery circuitry is required. On a hardware block implementing texture decompression, we observe 25% to 30% energy reduction at negligible quality loss (compared to the error introduced by the lossy compression algorithm). We investigate the strategy's performance under temperature and process variations and different assumptions on voltage-control circuitry. The strategy automatically chooses the lowest appropriate voltage, and thus the largest energy reduction, for each individual manufactured instance of the circuit.