Miracle-dz/UniFAR-FTUs huggingface dataset:
JAZ repressors of metabolic defense promote growth and reproductive fitness in Arabidopsis

Significance The plant hormone jasmonate promotes resistance to plant-eating organisms, ranging from pathogenic microbes to mammals. Jasmonate reprograms metabolism to fuel the production of diverse defense compounds and simultaneously inhibits plant growth. Understanding how growth is influenced across a range of defense levels remains unclear, but has important implications for optimizing crop productivity. Using a genetic approach to “tune” the jasmonate response, we assessed the physiological consequences of discrete levels of defense throughout the plant life cycle. Overactivation of jasmonate response led to carbon starvation, near loss of seed production and, under extreme conditions, lethality. Our findings explain the emergence of diverse strategies to keep jasmonate responses at bay and provide new insights into metabolic processes that underlie growth–defense trade-offs. Plant immune responses mediated by the hormone jasmonoyl-l-isoleucine (JA-Ile) are metabolically costly and often linked to reduced growth. Although it is known that JA-Ile activates defense responses by triggering the degradation of JASMONATE ZIM DOMAIN (JAZ) transcriptional repressor proteins, expansion of the JAZ gene family in vascular plants has hampered efforts to understand how this hormone impacts growth and other physiological tasks over the course of ontogeny. Here, we combined mutations within the 13-member Arabidopsis JAZ gene family to investigate the effects of chronic JAZ deficiency on growth, defense, and reproductive output. A higher-order mutant (jaz decuple, jazD) defective in 10 JAZ genes (JAZ1–7, -9, -10, and -13) exhibited robust resistance to insect herbivores and fungal pathogens, which was accompanied by slow vegetative growth and poor reproductive performance. Metabolic phenotypes of jazD discerned from global transcript and protein profiling were indicative of elevated carbon partitioning to amino acid-, protein-, and endoplasmic reticulum body-based defenses controlled by the JA-Ile and ethylene branches of immunity. Resource allocation to a strong defense sink in jazD leaves was associated with increased respiration and hallmarks of carbon starvation but no overt changes in photosynthetic rate. Depletion of the remaining JAZ repressors in jazD further exaggerated growth stunting, nearly abolished seed production and, under extreme conditions, caused spreading necrotic lesions and tissue death. Our results demonstrate that JAZ proteins promote growth and reproductive success at least in part by preventing catastrophic metabolic effects of an unrestrained immune response.
Increasing Information Visualization Compliance in Self-service Business Intelligence with User Assistance Systems

Self-Service Business Intelligence (SSBI) is increasingly used in organizations. While enabling layper-sons in report design to create their own reports in a timely manner, studies show that Business In-formation Visualization (BIV) is often inappropriately applied in these reports. This may lead decision makers to wrong conclusions. As a result, companies start to establish BIV governance frameworks, which employees are expected to comply with when designing reports. For this, they often provide employees with documentations about which guidelines to comply with. However, since employees may perceive this as additional effort with limited benefit, they may opt to simply not comply. If they are instead equipped with software that provides the functionality to comply, this software often lacks a description of the benefits of this compliance. To overcome this, user assistance systems (UAS) could be used, since they may both reduce the effort to comply as well as describe the usefulness of compli-ance. To investigate this issue, we developed a prototypical UAS for BIV, suggest a design for a la-boratory experiment, and present findings from a first preliminary study. Results indicate that using UAS for BIV may lead to increased perceived ease of use and perceived usefulness of complying with BIV guidelines.
THE OPTIMAL NUMBER OF HOSPITAL BEDS UNDER UNCERTAINTY: A COSTS MANAGEMENT APPROACH

Equipping hospital beds uses a great deal of a hospital''''s resources. Therefore, it is essential to consider the hospital beds'''' efficiency. To increase its efficiency, a fuzzy unrestricted model for managing hospital expenses is presented in this paper. The lack of beds in hospitals leads to patients’ admission loss and consecutively profit loss. On the other hand, increasing the bed count leads to an increase in equipment expenses. Therefore, in order to determine optimal bed capacity, it is of utmost importance to consider these two costs simultaneously. In our paper, hospital admission system is modeled with a multi-server queuing system (M/M/K). Therefore, to calculate the total cost function, limiting probabilities of multi-server queueing model is used. Furthermore, due to uncertain nature of parameters, such as interest rate and hospitalization profit in various future time periods, these uncertainties are covered by fuzzy logic. Finally, to determine the optimal bed count, Lee and Li''''s fuzzy ranking method is used. This model is implemented ona case study. Its goal is to determine the optimal bed count for emergency unit of Razi hospital in Torbat Heydarieh. Considering the high capability of Markovian chains in modeling different circumstances and the various queueing models, the proposed model can be extended for various hospital units.
A Field Application Measuring Healthcare Employees’ Perceptions Toward Corporate Entrepreneurship

Today, organizations that not only develop new and creative ideas, but that also offer new services to customers are able to continuously renew themselves and become leaders in high-competition environments. Organizations that offer new products and services to their customers might be able to survive, grow, achieve their goals, meet customer demands, and thus they obtain a great advantage. Therefore, the success and survival of today’s healthcare organizations within a highly competitive environment may be achieved by adopting continuous innovation as a core competence. It is necessary for organizations to be leaders in innovation in order to increase the value of healthcare services. Innovations generated in healthcare services will create both value for patient and competitive advantage for organization. Consequently, the phenomenon of corporate entrepreneurship underlies offering new services in the healthcare sector and being a leader. This study aims to determine which factors influence the perceptions toward corporate entrepreneurship held by doctor groups and nurse groups working in a University Hospital Research and Application Center, which might be seen as a pioneering example of “corporate entrepreneurship” in Turkey. The questionnaire form used in the study, of whose reliability coefficient was found to be . 884, shows consistency with prior studies conducted using the conceptual dimensions of the corporate entrepreneurship interaction model, and indicates statistically significant findings. Thus, in this study, the phenomenon of corporate entrepreneurship, which constitutes the conceptual framework of this study, will be explained in a theoretical dimension. Moreover, the methodology, findings, conclusion, and recommendations will be discussed.
AUTOMATED RECOGNITION OF STUTTER INVARIANCE OF LTL FORMULAS

Formal verification is the growing field of formalizing and verifying specifications for hardware and software systems. One such technique, known as model checking, can exhaustively check a software model for properties written in a specification language, such as Linear Temporal Logic (LTL). For large systems, memory reduction techniques are often used to complete a verification with the available hardware. One reduction technique, that of partial order reduction, has proven useful in aiding verifications, but it limits the expressiveness of LTL specifications. Due to the phenomenon of stuttered states in the model's reduced state graph representation, the LTL next operator is not guaranteed to produce correct results when partial order reduction is used. As more casual users begin using model checking, it is important to provide them with a convenient method of writing specifications that are known to be safe to use in the presence of partial order reduction. A description of how stuttered states are introduced and of a system of pat- terns for LTL formulas that are safe to use, despite the fact that they use the next operator, are given. To automatically determine if a formula matches one of the safe patterns, a Prolog based LTL recognizer which we developed is dis- cussed. A listing of the patterns of formulas recognized is given as an appendix.
First superburst from a classical low-mass X-ray binary transient

We report the analysis of the first superburst from a transiently accreting neutron star system with the All-Sky Monitor (ASM) on the Rossi X-ray Timing Explorer. The superburst occurred 55 days after the onset of an accretion outburst in 4U 1608-522. During that time interval, the accretion rate was at least 7% of the Eddington limit. The peak flux of the superburst is 22 to 45% of the Eddington limit, and its radiation energy output is between 4 × 10 41 and 9 × 10 41 erg for a distance of 3.2 kpc. Fits of cooling models to the superburst light curve indicate an ignition column depth between 1.5 × 10 12 and 4.1 × 10 12 gc m −2 . Extrapolating the accretion history observed by the ASM, we derive that this column was accreted over a period of 26 to 72. The superburst characteristics are consistent with those seen in other superbursting low-mass X-ray binaries. However, the transient nature of the hosting binary presents significant challenges for superburst theory, requiring additional ingredients for the models. The carbon that fuels the superburst is thought to be produced mostly during the accretion outbursts and destroyed in the frequent type-I X-ray bursts. Mixing and sedimentation of the elements in the neutron star envelope may significantly influence the balance between the creation and destruction of carbon. Furthermore, predictions for the temperature of the neutron star crust fail to reach the values required for the ignition of carbon at the inferred column depth.
Chronic, sublethal effects of high temperatures will cause severe declines in southern African arid-zone birds during the 21st century

Significance We synthesized physiological and behavioral data to evaluate the risks of acute, lethal effects of extreme heat events versus the sublethal costs of chronic exposure to sustained hot weather for birds inhabiting southern Africa’s Kalahari Desert over the course of the 21st century. The risk of mass mortality events similar to those predicted for the American southwest and sometimes observed in Australia will remain low for Kalahari birds. However, the sublethal costs of chronic exposure, manifested as progressive loss of body condition, delayed fledging, reduced fledging size, and outright breeding failure, will likely drive major population declines. We anticipate that much of the Kalahari’s avian biodiversity will be lost by the end of the century. Birds inhabiting hot, arid regions are among the terrestrial organisms most vulnerable to climate change. The potential for increasingly frequent and intense heat waves to cause lethal dehydration and hyperthermia is well documented, but the consequences of sublethal fitness costs associated with chronic exposure to sustained hot weather remain unclear. Using data for species occurring in southern Africa’s Kalahari Desert, we mapped exposure to acute lethal risks and chronic sublethal fitness costs under past, present, and future climates. For inactive birds in shaded microsites, the risks of lethal dehydration and hyperthermia will remain low during the 21st century. In contrast, exposure to conditions associated with chronic, sublethal costs related to progressive body mass loss, reduced nestling growth rates, or increased breeding failure will expand dramatically. For example, by the 2080s the region will experience 10–20 consecutive days per year on which Southern Pied Babblers (Turdoides bicolor) will lose ∼4% of body mass per day, conditions under which this species’ persistence will be extremely unlikely. Similarly, exposure to air temperature maxima associated with delayed fledging, reduced fledgling size, and breeding failure will increase several-fold in Southern Yellow-billed Hornbills (Tockus leucomelas) and Southern Fiscals (Lanius collaris). Our analysis reveals that sublethal costs of chronic heat exposure are likely to drive large declines in avian diversity in the southern African arid zone by the end of the century.
TLS Protocol Verification for Securing E-Commerce Websites

E-commerce security is very important especially nowadays but internet is entrusted due to the attacks and hackers exploitations. To improve the security of electronics transactions, many protocols are developed. SSL/TLS is the most commonly used, although many dangerous attacks were found. So, developers have to upgrade SSL/TLS to avoid these attacks and enhance security. To achieve their goals, hackers exploit flaws and errors found in SSL/TLS protocol implementations, it is necessary to verify and validate the security of the entire software code. Therefore, to improve the security of SSL/TLS protocol, researchers try to find solutions; protocols must therefore be tested and validated before their launch. In this paper, we will focus on analyzing SSL/TLS protocol with automated formal verification tool AVISPA. We study the renegotiation attack and try to detect it using AVISPA. We use formal models for automatic verification of security protocol to discover new attacks, to prevent similar attack in the future and also to increase the tool efficiency.
Contributions in face detection with deep neural networks

Face Detection is one of the most studied subjects in the Computer Vision field. Given an arbitrary image or video frame, the goal of face detection is to determine whether there are any faces in the image and, if present, return the image location and the extent of each face. Such a detection is easily done by humans, but it is still a challenge within Computer Vision. The high degree of variability and the dynamicity of the human face makes it an object very difficult to detect, mainly in complex environments. Recently, Deep Learning approaches started to be applied for Computer Vision tasks with great results. They opened new research possibilities in different applications, including Face Detection. Even though Deep Learning has been successfully applied for such a task, most of the state-of-the-art implementations make use of off-the-shelf face detectors and do not evaluate differences among them. In other cases, the face detectors are trained in a multitask manner that includes face landmark detection, age detection, and so on. Hence, our goal is threefold. First, we summarize and explain many advances of deep learning, detailing how each different architecture and implementation work. Second, we focus on the face detection problem itself, performing a rigorous analysis of some of the existing face detectors as well as implementations of our own. We experiment and evaluate variations of hyper-parameters for each of the detectors and their impact in different datasets. We explore both traditional and more recent approaches, as well as implementing our own face detectors. Finally, we implement, test, and compare a meta learning approach for face detection, which aims to learn the best face detector for a given image. Our experiments contribute in understanding the role of deep learning in face detection as well as the subtleties of changing hyper-parameters of the face detectors and their impact in face detection. We also show how well features obtained with deep neural networks trained on a general-purpose dataset perform on a meta learning approach for face detection. Our experiments and conclusions show that deep learning has indeed a notable role in face detection.
Experimental trampling of vegetation . II . Predictors of 1995 , 32 . 215-224 resistance and resilience *

1. Experimental trampling was conducted in 18 vegetation types in five separate mountain regions in the United States. Each type was trampled 0-500 times and vegetation response was assessed 2 weeks and 1 year after trampling 2. The response of vegetation to trampling is expressed terms of three indices: resistance, tolerance and resilience. Resistance and tolerance are determined from the vegetation surviving 2 weeks and 1 year after trampling, respectively. Resilience compares the change over the remainder of the year that during the first 2 weeks after trampling. 3. Plant morphological characteristics explained more of the variation in response to trampling than the site characteristics that were assessed: altitude, overstorey canopy cover or total groundlayer vegetation cover. 4. Resistance was primarily a function of vegetation stature, erectness and whether plants were graminoids, forbs or shrubs. The most resistant plants were caespitose or matted graminoids; the least resistant plants were erect forbs. 5. Resilience was primarily a function of whether plants were chamaephytes, with perennating buds located above the ground surface. Chaemaephytes were much less resilient than other plants. 6. Tolerance, which measures the ability of vegetation to withstand a cycle of disturbance and recovery, was correlated more with resilience than resistance Consequently, the least tolerant plants were the chamaephytes. The most tolerant plants were caespitose, matted and rosette hemicryptophytes and geophytes. 7. The resistance and resilience of individual species were negatively correlated, particularly for chamaephytes and graminoids. For herbaceous species with perennating tissues located at or below ground level, tolerance was more highly correlated with resilience than with resistance. For chamaephytes, tolerance was more highly correlated with resistance.
Crustal structure in the Lachlan Orogen 1 CRUSTAL COMPLEXITY IN THE LACHLAN OROGEN ! " REVEALED FROM TELESEISMIC RECEIVER # " FUNCTIONS $ "

+" There is an ongoing debate about the tectonic evolution of southeast Australia, ! " particularly about the causes and nature of its accretion to a much older Precambrian ! #" core to the west. Seismic imaging of the crust can provide useful clues to address this ! $" issue. Seismic tomography imaging is a powerful tool often employed to map elastic ! %" properties of the Earth’s lithosphere, but in most cases does not constrain well the depth ! &" of discontinuities such as the Mohorovi! i" (Moho). In this study, an alternative imaging ! '" technique known as receiver function (RF) has been employed for seismic stations near ! (" Canberra in the Lachlan Orogen to investigate: (i) the shear wave velocity profile in the ! )" crust and uppermost mantle, (ii) variations in the Moho depth beneath the Lachlan ! *" Orogen, and (iii) the nature of the transition between the crust and mantle. A number of #+" styles of RF analyses were conducted: H-K stacking to obtain the best compressional#! " shear velocity (VP/VS) ratio and crustal thickness; non-linear inversion for the shear ##" wave velocity structure and inversion of the observed variations in RFs with back#$" azimuth to investigate potential dipping of the crustal layers and anisotropy. #%" The thick crust (up to 48 km) and the mostly intermediate nature of the crust-mantle #&" transition in the Lachlan Orogen could be due to the presence of underplating at the #'" base of the crust, and possibly to the existing thick piles of Ordovician mafic rocks #(" present in the mid and lower crust. Results from numerical modelling of receiver #)" functions at 3 seismic stations (CAN, CNB and YNG) suggest that the observed #*" variations with back-azimuth could be related to a complex structure beneath these $+" stations with the likelihood of both a dipping Moho and crustal anisotropy. Our analysis $! " reveals crustal thickening to the west beneath CAN station which could be due to slab $#" convergence. The crustal thickening may also be related to the broad Macquarie $$" Crustal structure in the Lachlan Orogen 3 volcanic arc, which is rooted to the Moho. The crustal anisotropy may arise from a $%" strong N-S structural trend in the eastern Lachlan Orogen and to the preferred $&" crystallographic orientation of seismically anisotropic minerals in the lower and middle $'" crust related to the palaeo-Pacific plate convergence. $("
Chemical Modification of Nanocellulose in Wood Adhesive: Review

Bio-based nanomaterial is more attractive, due to its abundance, eco-friendliness and sustainability, when compared to the non-renewable toxic petrochemicals used in the wood adhesive sector. Recent studies on the formaldehyde emission by petrochemical binders in wood adhesives have attracted scientists for the research in biomaterial-based binders. In this aspect nanocellulose (NC) is one such material which has reinforcing ability and has natural binding properties. Conventional wood adhesive uses petrochemical-based binders and additives. Inclusion of nanocellulose in wood adhesive could drastically reduce the dependency on non-renewable petroleum sources. Even though wood adhesive uses NC for improving mechanical properties of the adhesive, usage is restricted because of its inability to enhance tackiness and adhesion compared with petrochemicals. Availability of free hydroxyl groups and feasibility for modification can be a potential way for functionalization of this nanomaterial. To improve adhesion properties and to make nanocellulose act as a functional filler, the crosslinking approach can be a possible solution. Enhancement of thermal properties with improved thermal degradation, water barrier properties of crosslinked films and enhanced mechanical properties especially in crosslinked poly (vinyl alcohol) (PVA) matrix, which is one of the binders for wood adhesive discussed in this review paper proves the potential applicability of crosslinked NC. Hence by inclusion of NC in wood adhesive and crosslinking with the binder, both mechanical and performance properties are expected to enhance which will create a new world and possibilities for the bio-based eco-friendly wood adhesives. In this review paper, we have reviewed the crosslinking of nanocellulose to enhance the performance of wood adhesives.
An Intuitive Approach for Web Scale Mining using W-Miner for Web Personalization

— Web usage mining performs mining on web usage data or web logs. It is now possible to perform data mining on web log records collected from the web page history. A web log is a listing of page reference data/click stream data. The behavior of the web page readers is imprinted in the web server log files. By looking at the sequence of pages a user accesses, a user profile could be developed thus aiding in personalization. With personalization, web access or the contents of web page are modified to better fit the desires of the user and also to identify the browsing behavior of the user can improve system performance, enhance the quality and delivery of Internet Information services to the end user and identify the population of potential customers. With clustering, the desires are determined based on similarities. In this study, a Fuzzy clustering algorithm is designed and implemented. For the proposed algorithm, meaningful behavior patterns are extracted by applying efficient Fuzzy clustering algorithm, to log data. It is proved that performance of the proposed system is better than that of the existing best algorithm. The proposed Fuzzy clustering w-miner algorithm can provide popular information to web page visitors.