Miracle-dz/UniFAR-FTUs huggingface dataset:
Is it a short-memory, long-memory, or permanently Granger-causation influence?

Exploring the Granger-causation relationship is an important and interesting topic in the field of econometrics. In the traditional model we usually apply the short-memory style to exhibit the relationship, but in practice there could be other different influence patterns. Besides the short-memory relationship, Chen (2006) demonstrates a long-memory relationship, in which a useful approach is provided for estimation where the time series are not necessarily fractionally co-integrated. In that paper two different relationships (short-memory and long-memory relationship) are regarded whereby the influence flow is decayed by geometric, or cutting off, or harmonic sequences. However, it limits the model to the stationary relationship. This paper extends the influence flow to a non-stationary relationship where the limitation is on −0.5 ≤ d ≤ 1.0 and it can be used to detect whether the influence decays off (−0.5 ≤ d < 0.5) or is permanent (0.5 ≤ d ≤ 1.0). Copyright © 2008 John Wiley & Sons, Ltd.
A Review on Eco-Friendly Natural Plant and Animal Products for Plant Diseases Management

India is the second most populous country in the world. With the increasing population, the cultivable land resource is shrinking day to day. To meet the food, fibre, fuel, fodder and other needs of the growing population, the productivity of agricultural land and soil health needs to be improved. Green Revolution in the post-independence era has shown path to developing countries for selfsufficiency in food but sustaining agricultural production against the finite natural resource base demands has shifted from the ―resource degrading‖ chemical agriculture to a ―resource protective‖ biological or sustainable International Journal of Current Microbiology and Applied Sciences ISSN: 2319-7706 Volume 8 Number 08 (2019) Journal homepage: http://www.ijcmas. com
Option pricing under threshold autoregressive models by threshold Esscher transform

This paper develops a valuation model for options under the class of self-exciting threshold autoregressive (SETAR) models and their variants for the price dynamics of the underlying asset using the self-exciting threshold autoregressive Esscher transform (SETARET). In particular, we focus on the first generation SETAR models first proposed by Tong (1977, 1978) and later developed in Tong (1980, 1983) and Tong and Lim (1980), and the second generation models, including the SETAR-GARCH model proposed in Tong (1990) and the double-threshold autoregressive heteroskedastic time series model (DTARCH) proposed by Li and Li (1996). The class of SETAR-GARCH models has the advantage of modelling the non-linearity of the conditional first moment and the varying conditional second moment of the financial time series. We adopt the SETARET to identify an equivalent martingale measure for option valuation in the incomplete market described by the discrete-time SETAR models. We are able to justify our choice of probability measure by the SETARET by considering the self-exciting threshold dynamic utility maximization. Simulation studies will be conducted to investigate the impacts of the threshold effect in the conditional mean described by the first generation model and that in the conditional variance described by the second generation model on the qualitative behaviors of the option prices as the strike price varies.
Up-regulation of miR-149 by E-cadherin inhibits breast cancer cell invasion and migration

Breast cancer is a malignant tumor with relatively good prognosis in women, but tumor recurrence and distant metastasis is the important cause of death in patients with breast cancer[1]. Micro RNA (microRNA, miRNA) is a kind of non-coding RNA, and it plays an important role in the occurrence and development of tumor, and plays a regulatory role of a wide variety in tumor biological behaviors[2-4]. Luo et al[5] reported that miR-14 may play the role of tumor suppressor genes and could inhibit hepatocellular carcinoma metastasis. There are few researches about miR-149 in the breast cancer at home and abroad, therefore, this study investigate the effects and possible mechanism of MicroRNA (miR)-149 expression and over-expression in breast cancer cells on their invasion and migration.
11 RFID Applications for Sanitary Environments

Healthcare represents one of the most significant sectors where the diffusion of RFID technology is growing day by day. Many different applications have already been studied and developed, with both active and passive devices working at all the available operative frequencies. Sanitary environments are nowadays extremely complex structures employing several thousands of people with very strict safety requirements: in emergency situations for example 5 minutes can make the difference for a patient between survive and die. RFID is especially indicated to be employed in these scenarios for two main reasons: first of all because it’s a particularly reliable technology, with good performances, few errors and fast interaction, and secondly because, due to the presence of many different technological systems, ad-hoc solutions can be designed on the specific requirements of the application to be realized. At present the most common RFID applications in healthcare can be divided into two main categories: the items tracking and the tracking and identification of people, patients and sanitary operators. The items tracking is performed in order to avoid the loss of expensive devices and to reduce wasting of time during assistance operations: systems studied and realized for this purpose cover all the range of RFID systems and provide different services according to their different performances. Passive systems are mainly thought for the tracking of large amounts of items, providing identification also to low value items, and are mainly based on gate structures. Active systems are designed for the tracking of big and expensive items and use long range antennas located at specific key points. RFID systems for the identification of people probably represent the most interesting sector, due to the variety of different applications that can be studied and realized. The most common systems foresee the use of RFID for the tracking of sanitary operators or patients during their assistance operations: these solutions are very similar to the one described for the tracking of items and are already working in many structures around the world. Along with this many other applications have been implemented, including systems operating the unambiguous matching between the patient and his treatments (for example the medicine or the blood sack) or between the mother and the child in the paediatrics departments: these applications mainly foresee the use of passive technology, due to the lower costs, and adhoc items like electronic bracelets have already been realized and can be commonly found off the shelf. Finally the availability of a memory on the transponders fostered to the use of RFID technology also as a mean to promptly store and retrieve patient related information: for example electronic case history or electronic medical prescription applications have been studied and developed.
Title : An Electrophysiological Study of Attention Capture : Does Rarity Enable Capture ?

approved: ______________________________________________________ Mei-Ching Lien Several behavioral studies have suggested that rarity is critical for enabling irrelevant, salient objects to capture attention. We tested this hypothesis using the event-related potential (ERP) component, N2pc, thought to reflect attentional allocation. A cue display was followed by a target display in which participants identified the letter in a specific color. Experiment 1 pitted rare, irrelevant abrupt onset cues (appearing on only 20% of trials) against target-relevant color cues. The relevant color cue produced large N2pc and cue validity effects, even when competing with a rare, salient, simultaneous abrupt onset. Similar results occurred even when abrupt onset frequency was reduced to only 10% of trials (Experiment 2). Experiment 3 examined rare, irrelevant color singleton cues (20% of trials). Despite being rare and salient, these singleton cues produced no N2pc or cue validity effect, indicating little attentional capture. Experiments 4a and 4b greatly increased color cue salience by adding 4 background boxes, increasing color contrast, and tripling the cue display duration (from 50 to 150 ms). Small cue validity and N2pc effects were obtained, but did not strongly depend on degree of rarity (20% vs. 100%). We argue that rarity by itself is neither necessary nor sufficient to produce attention capture.
Materials science and engineering: New vision in the era of artificial intelligence

Scientific discovery evolves from the experimental, through the theoretical and computational, to the current data-intensive paradigm. Materials science is no exception, especially for computational materials science. In recent years, great achievements have been made in the field of materials science and engineering (MSE). Here, we review the previous paradigms of materials science and some classical MSE models. Then, our data-intensive MSE (DIMSE) model is proposed to reshape future materials innovations. This work will help to address the global challenge for materials discovery in the era of artificial intelligence (AI), and essentially contribute to accelerating future materials continuum.
Training Data Voids: Novel Attacks Against NLP Content Moderation

Machine learning-based content moderation systems make classification decisions by leveraging patterns learned from training data. However, patterns that are under or unrepresented in a system’s training data —which we call training data voids— cannot be learned and may be exploited by adversarial users to confuse the system. Specifically, adversarial users may creatively construct harmful content that differ from known training examples, leading to uncertain classification. Here, we call this type of attack against machine learning classifiers a novelty attack and distinguish it from a more widely known class of attacks (i.e., adversarial attacks). Additionally, we contribute a study design for exploring the extent to which novel harmful content can be constructed and for characterizing the effects of novelty on classification results in several text-based content moderation Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from permissions@acm.org. CSCW ’19, Nov. 09–13, 2019, Austin, TX © 2019 Association for Computing Machinery. ACM ISBN 978-1-4503-9999-9/18/06. $15.00 https://doi.org/10.1145/1122445.1122456 Training Data Voids: Novel Attacks Against NLP Content Moderation CSCW ’19, Nov. 09–13, 2019, Austin, TX domains. The findings of this study are important for highlighting a potential vulnerability of machine learning-based content moderation systems and may suggest that such systems will remain limited in the near future. We propose that including human intelligence in content moderation systems may be an effective approach for mitigating potential exploitation.
Simulating the ocean’s chlorophyll dynamic range from coastal upwelling to oligotrophy

The measured concentration of chlorophyll a in the surface ocean spans four orders of magnitude, from ∼0.01mgm−3 in the oligotrophic gyres to>10mgm−3 in coastal zones. Productive regions encompass only a small fraction of the global ocean area yet they contribute disproportionately to marine resources and biogeochemical processes, such as fish catch and coastal hypoxia. These regions and/or the full observed range of chlorophyll concentration, however, are often poorly represented in global earth system models (ESMs) used to project climate change impacts on marine ecosystems. Furthermore, recent high resolution (∼10 km) global earth system simulations suggest that this shortfall is not solely due to coarse resolution (∼100 km) of most global ESMs. By integrating a global biogeochemical model that includes two phytoplankton size classes (typical of many ESMs) into a regional simulation of the California Current System (CCS) we test the hypothesis that a combination of higher spatial resolution and enhanced resolution of phytoplankton size classes and grazer linkages may enable global ESMs to better capture the full range of observed chlorophyll. The CCS is notable for encompassing both oligotrophic (< 0.1mgm−3) and productive (> 10mgm−3) endpoints of the global chlorophyll distribution. As was the case for global high-resolution simulations, the regional high-resolution implementation with two size classes fails to capture the productive endpoint. The addition of a third phytoplankton size class representing a chain-forming coastal diatom enables such models to capture the full range of chlorophyll concentration along a nutrient supply gradient, from highly productive coastal upwelling systems to oligotrophic gyres. Weaker ‘top-down’ control on coastal diatoms results in stronger trophic decoupling and increased phytoplankton biomass, following the introduction of new nutrients to the photic zone. The enhanced representation of near-shore chlorophyll maxima allows the model to better capture coastal hypoxia along the continental shelf of the North American west coast and may improve the representation of living marine re-
Total aerosol effect: forcing or radiative flux perturbation

Uncertainties in aerosol forcings, especially those associated with clouds, contribute to a large extent to uncertainties in the total anthropogenic forcing. The interaction of aerosols with clouds and radiation introduces feedbacks which can affect the rate of rain formation. Traditionally these feedbacks were not included in estimates of total aerosol forcing. Here we argue that they should be included because these feedbacks act quickly compared with the time scale of global 5 warming. We show that for different forcing agents (aerosols and greenhouse gases) the radiative forcings as traditionally defined agree rather well with estimates from a method, here referred to as radiative flux perturbations (RFP), that takes these fast feedbacks and interactions into account. Thus we propose replacing the direct and indirect aerosol forcing in the IPCC forcing chart with RFP estimates. This implies that it is better to evaluate the total anthropogenic aerosol effect as a 10 whole.
Raven: A Tool for Automatic Generation of Analog Behavioral Models from Schematics

Analog content in SOCs is increasing every generation as these systems due to increasing support for consumer electronics and increasing IO and graphics bandwidth. Since these circuits are part of a larger digital system, the analog-digital interactions must be verified, typically via suitable RTL level abstractions of the analog blocks. Due to the lack of any formal equivalence checking of analog circuits with their higher level RTL models, mixed-signal validation (MSV) is used extensively to verify correctness of the digital and analog sub-systems working together. Figure 1 shows a comparison of an all digital validation flow with a mixed-signal validation flow. The analog models in an MSV flow typically come in three flavors: spice-level schematic netlists, Verilog-AMS (analog mixed-signal), and Verilog with real numbers (abbreviated as Verilog-Real in rest of this abstract) – with the latter two referred to as behavioral models or BMODs in short. The schematic models are the slowest to simulate but are most accurate and the Verilog-Real models are the fastest to simulate with some loss in accuracy. At least an order of magnitude speedup across each level is typical as we move from schematic to Verilog-AMS to Verilog-Real models. Figure 1. A comparison of digital validation flow with mixed-signal validation flow Typically, the BMODs are created by a validation engineer manually after reading the often incomplete micro-architecture and circuit specification documents and talking to the analog design engineers (DEs). The lack of automated BMOD creation in existing flows results in the following disadvantages:  Incomplete and inconsistent modeling of analog circuits the quality of the BMODs depends on the skill of the validation engineer, the completeness of documentation, and time spent in model creation.  Diminished productivity of validation engineers since model creation takes significant time away from other validation tasks such as test plan writing, worst-case scenario generation etc.  Lack of process, voltage, and temperature (PVT) awareness in the models – existing models are typically created for one PVT point and therefore do not provide good coverage for circuits like thermal sensors, whose behavior at different temperatures must be verified.  Outdated models – design changes are not tracked in the BMOD since, depending on the change, the validation engineer has to re-create the model which involves significant time and effort. To alleviate these problems, we have created a tool called Raven that automates BMOD creation from schematics. The overall flow using Raven is shown in Figure 2. Raven takes as input the circuit schematic (spice or equivalent format) and the circuit specification file. Currently, Raven supports Verilog-Real output and we DIGITAL WORLD ANALOG WORLD uArch/circuit Specification (MAS/CAS) System Verilog RTL VerilogAMS Verilog with real Schematic Netlist Schematic Netlist Synthesis or manual coding Manual coding Circuit Design & Extraction Manual coding
How are we doing?: Presenting System Confidence Information to Support Trust Calibration and Adaptive Function Allocation

The “strong but silent” design of many decision support systems (DSS) has contributed to problems such as automation bias and trust miscalibration. The present study examined whether these difficulties can be overcome by providing continually updated information regarding a system's confidence in its own ability to perform its task(s) accurately and reliably. The application domain for this research was in-flight icing. Two groups of pilots flew a motion-based simulator in simulated icing conditions and were assisted by a neural net-based DSS that detected, and identified the location of, ice accretion. One group of pilots received information about overall system reliability only, whereas a second group was presented with a trend display of system confidence. Pilots in the latter group were better calibrated in terms of when to follow the system's advice. They were also more likely to reverse their actions when system-recommended actions were unsuccessful. Consequently, they experienced fewer icing-induced stalls. The findings from this research will be discussed in terms of their implications for the design of decision aids and for adaptive function allocation in human-machine teams.
Effects of Enrichment Planting with Five Native Species and Different Plantation Treatments on Seedling Growth Characteristics at Logged-over Forest in Lao PDR

Enrichment planting is commonly used for increasing the density of tree species in secondary forests and one of forest rehabilitation programs in Lao PDR. This study aimed to determine the performance of five native species in enrichment planting using different canopy opening treatments, and to examine the suitable species and silviculture techniques applicable to a logged-over forest in Lao PDR. Results of the study showed that only crown height had significant difference among species and planting treatments. The survival rate and crown diameter were significantly different by species, but not by planting treatments. However, root collar diameter (RCD) and height of seedlings showed significant differences among planting treatments. Among the study species, Hopea odorata and Dalbergia cochinchinensis showed significantly higher survival rate and height growth, indicating their suitability in enrichment planting for rehabilitation of forest in Lao PDR. The results also suggested that 2 m width line planting stimulated RCD growth, but wider line planting, such as gap planting, promoted height growth of seedlings.
Presence and Natural Treatment of Organic Micropollutants and their Risks after 100 Years of Incidental Water Reuse in Agricultural Irrigation

The aim of the research was to show the presence of micropollutants contained in the wastewater of Mexico City within the distribution canals of the Mezquital Valley (MV), as well as their retention in agricultural soil and aquifers. This system constitutes the world's oldest and largest example of the use of untreated wastewater for agricultural irrigation. The artificial recharge associated with the MV aquifers, with groundwater extracted for human consumption showing its importance as a water resource for Mexico City. The results of sampling show the presence of 18 compounds, with 10 of these considered as endocrine disruptor compounds (EDCs). The concentration of these pollutants ranged from 2 ng/L for 17 β-estradiol to 99 ng/L for DEHP, with these values decreasing throughout the course of the canals due to the wastewater dilution factor, their retention in agricultural soil, and their accumulation in the local aquifer. The main mechanisms involved in natural attenuation are adsorption, filtration, and biodegradation. Drinking water equivalent levels (DWELs) were estimated for 11 compounds with regard to acceptable daily intakes (ADIs), by assuming local exposure parameters for a rural Mexican population. These were compared with the maximum groundwater concentrations (Cgw) to screen the potential risks. The very low ratios of Cgw to DWELs indicate no appreciable human health risk from the presence of trace concentrations of these compounds in the source of drinking water in the MV. Despite this, far from being exceeded after more than 100 years of irrigation with residual water, the natural soil attenuation seems to remain stable.
Examining The Dynamics of Cooperation Between Competing Firms in Their R&D Activities (R&D Co-Opetition)

The relationship between collaboration with competitors and goods innovation performance was investigated along with the moderating effect of the innovating firm's technological capability. The hypothesis that collaboration with competitors has an inverted U-shaped relationship with goods innovation performance was tested using data on new goods introductions from 749 Iranian firms. The results support the balance between competition and collaboration by confirming that collaboration with competitors contributes considerably to successful goods innovation. The positive influences of co-optation certainly seem consistent with the cooperative arguments that collaboration with competitors increases absorptive capacity, improves information exchange and facilitates joint problem solving. The results also show that unnecessary collaboration with competitors can have a negative influence on innovation performance, raising concerns about opportunistic exploitation. The results support the existence of a bell-shaped relationship between application and goods innovation performance. Technological capability and alliances with universities were shown to weaken the relationship.