Miracle-dz/UniFAR-FTUs huggingface dataset:
Variation in reproductive success within a subtropical fig/pollinator mutualism

Plants pollinated by specialists are often thought to receive exceptionally high-quality pollinator service, but in relatively low and unpredictable quantities. We examine and reject this hypothesis for an obligate mutualism between a subtropical New World fig (Ficus aurea) and its species-specific pollinator (Pegoscapus jimenezi). Fig wasps lay eggs within the flowers they pollinate; their offspring destroy a large proportion of fig's seeds. In a 6-year study of this interaction in Florida, U.S.A. , we found that pollination intensity was in fact relatively high. Also contrary to expectations, reproductive success of both mutualists (as well as other wasps cohabiting the figs) was extremely variable and generally low, at three different scales of sampling: among figs from a single crop of one tree (thirty-four figs), among crops produced at different times by that tree (126 figs), and across trees over a 1-year period (379 figs). Although variable, fig contents were not completely unpredictable. For example, seed and wasp numbers increased with the number of flowers in a fig, and female and male flower numbers increased together. Little is yet known about the causes either of these relationships or of the massive fig-to-fig variation itself, although there is some evidence that they exist in other fig species as well. Further investigations of these patterns should shed new light on the ecology and evolution of this mutualism.
TERRORISM ACTIVITIES AND CAPITAL FLOWS OF DEVELOPED COUNTRIES IN THE WORLD

Main aim of paper is to empirically measure the consequences of terrorism activities on capital flows of developed countries of the world. Capital flows are interpreted as FDI inflows and outflows of developed countries. The methodology is based on dynamic panel data models (System-2 step-GMM estimator) using sample covering up to 36 developed countries all over the world (Europe, America, Asia, Oceania) from 2000 to 2016. The key results indicate that terrorism incidents, economical and institutional variables are found to have different impact on capital flows of developed countries. All used variables of the model will show the level of their impact of capital flows. The results indicate that terrorist activities weaken economic activity of a country while minimizing capital flows in certain situations. The recommendations and proposals are given based on the results of research.
Learning automata and sigma imperialist competitive algorithm for optimization of single and multi-objective functions

Evolutionary Algorithms (EA) consist of several heuristics which are able to solve optimisation tasks by imitating some aspects of natural evolution. Two widely-used EAs, namely Harmony Search (HS) and Imperialist Competitive Algorithm (ICA), are considered for improving single objective EA and Multi Objective EA (MOEA), respectively. HS is popular because of its speed and ICA has the ability for escaping local optima, which is an important criterion for a MOEA. In contrast, both algorithms have suffered some shortages. The HS algorithm could be trapped in local optima if its parameters are not tuned properly. This shortage causes low convergence rate and high computational time. In ICA, there is big obstacle that impedes ICA from becoming MOEA. ICA cannot be matched with crowded distance method which produces qualitative value for MOEAs, while ICA needs quantitative value to determine power of each solution. This research proposes a learnable EA, named learning automata harmony search (LAHS). The EA employs a learning automata (LA) based approach to ensure that HS parameters are learnable. This research also proposes a new MOEA based on ICA and Sigma method, named Sigma Imperialist Competitive Algorithm (SICA). Sigma method provides a mechanism to measure the solutions power based on their quantity value. The proposed LAHS and SICA algorithms are tested on wellknown single objective and multi objective benchmark, respectively. Both LAHS and MOICA show improvements in convergence rate and computational time in comparison to the well-known single EAs and MOEAs.
Poseidon: A New Hash Function for Zero-Knowledge Proof Systems

The area of practical computational integrity proof systems, like SNARKs, STARKs, Bulletproofs, is seeing a very dynamic development with several constructions having appeared recently with improved properties and relaxed setup requirements. Many use cases of such systems involve, often as their most expensive part, proving the knowledge of a preimage under a certain cryptographic hash function, which is expressed as a circuit over a large prime ﬁeld. A notable example is a zero-knowledge proof of coin ownership in the Zcash cryptocurrency, where the inadequacy of the SHA-256 hash function for such a circuit caused a huge computational penalty. In this paper, we present a modular framework and concrete instances of cryptographic hash functions which work natively with GF ( p ) objects. Our hash function P OSEIDON uses up to 8x fewer constraints per message bit than Pedersen Hash. Our construction is not only expressed compactly as a circuit, but can also be tailored for various proof systems using specially crafted polynomials, thus bringing another boost in performance. We demonstrate this by implementing a 1-out-of-a-billion membership proof with Merkle trees in less than a second by using Bulletproofs.
Temperature sensitivity and freezing resistance among isolates of Typhula ishikariensis from Russia

TAMOTSU HOSHINO Hokkaido National Industrial Research Institute, 2-17-2-1, Tsukisamu-higashi, Toyohira-ku, Sapporo 062-8517, Japan OLEG B. TKACHENKO Main Botanical Garden, Russian Academy of Sciences, Botanicheskaya ul. 4, Moscow, 127276, Russia ANNE MARTE TRONSMO Norwegian Crop Research Institute, Fellesbygget, N-1432, Ås, Norway AKIRA KAWAKAMI Hokkaido National Experiment Station, 1 Hitsujigaoka, Toyohira-ku, Sapporo 062-8555, Japan NAKOI MORITA SATORU OHGIYA KOZO ISHIZAKI Hokkaido National Industrial Research Institute, 2-17—2-1, Tsukisamu-higashi, Toyohira-ku, Sapporo 062-8517, Japan and NAOYUKI MATSUMOTO National Institute of Agro-Environmental Sciences, 3-1-1, Kannondai, Tsukuba 305-0856, Japan
Title Exploring surface cleaning strategies in hospital to prevent contact transmission of methicillin-resistant Staphylococcus aureus

Background: Cleaning of environmental surfaces in hospitals is important for the control of methicillin-resistant Staphylococcus aureus (MRSA) and other hospital-acquired infections transmitted by the contact route. Guidance regarding the best approaches for cleaning, however, is limited. Methods: In this study, a mathematical model based on ordinary differential equations was constructed to study MRSA concentration dynamics on high-touch and low-touch surfaces, and on the hands and noses of two patients (in two hospitals rooms) and a health care worker in a hypothetical hospital environment. Two cleaning interventions – whole room cleaning and wipe cleaning of touched surfaces – were considered. The performance of the cleaning interventions was indicated by a reduction in MRSA on the nose of a susceptible patient, relative to no intervention. Results: Whole room cleaning just before first patient care activities of the day was more effective than whole room cleaning at other times, but even with 100% efficiency, whole room cleaning only reduced the number of MRSA transmitted to the susceptible patient by 54%. Frequent wipe cleaning of touched surfaces was shown to be more effective that whole room cleaning because surfaces are rapidly re-contaminated with MRSA after cleaning. Wipe cleaning high-touch surfaces was more effective than wipe cleaning low-touch surfaces for the same frequency of cleaning. For low wipe cleaning frequency (≤3 times per hour), high-touch surfaces should be targeted, but for high wipe cleaning frequency (>3 times per hour), cleaning should target highand low-touch surfaces in proportion to the surface touch frequency. This study reproduces the observations from a field study of room cleaning, which provides support for the validity of our findings. Conclusions: Daily whole room cleaning, even with 100% cleaning efficiency, provides limited reduction in the number of MRSA transmitted to susceptible patients via the contact route; and should be supplemented with frequent targeted cleaning of high-touch surfaces, such as by a wipe or cloth containing disinfectant.
An Investigation of Individual Willingness to Use Ride-Hail Versus Transit

Problem, research strategy, and findings: Few studies have examined ride-hail users’ individual preferences between ride-hail and transit. Based on a survey of ride-hail users in the Philadelphia (PA) region, I examine who uses ride-hail and investigate ride-hail users’ willingness to use ride-hail versus transit. My results suggest that more than one-quarter of respondents replaced transit with ride-hail in their last ridehail trips. Mixed logit regression analysis based on stated preference choice experiments indicate that higher-income respondents and respondents over 30 years old are increasingly willing to choose ride-hail over transit, even though their actual ride-hail usage is lower than that among lower-income and younger respondents. Results also show that female respondents are more willing to choose ride-hail over transit than male respondents and less frequent transit users are more likely to choose ride-hail than frequent transit users. Higher cost and longer trip duration are significant deterrents for travel by either mode. Respondents consider the time spent on walking to and from transit more burdensome than in-vehicle travel time and wait time for transit and ride-hail. They consider waiting for ride-hail less burdensome than waiting for transit. Survey sampling and design limitations provide lessons for future ride-hail studies. Takeaway for practice: Practitioners should ensure convenient, affordable travel options for lowerincome residents, who are more frequent but less willing ride-hail users than higher-income residents. Female respondents’ safety concerns about transit should urge transit agencies to recognize female transit riders’ travel needs. The relationship between age and willingness to use ride-hail reminds planners to anticipate greater substitution of ride-hail for transit as the more tech-savvy generation starts entering their 30s. Last, fare reduction alone may not be enough to prompt ride-hail users to switch to transit. Service improvements that shorten the overall trip duration are imperative to make transit more attractive.
The relationship between self-compassion and chronic depression: a
 cross-sectional clinical study

Background: At present, depression is the world’s most common psychopathology. Self-compassion is a psychological concept that has shown promise regarding its impact on psychopathology. Despite a vast literature studying the relationship between depression and self-compassion, few studies about this association were done in clinical samples.Goals: This study sought to analyze the associations between self-compassion, its dimensions and symptomatology of depression, during and after a therapeutic intervention.Methods: A non-probabilistic sampling method was used. All participants had been diagnosed with persistent depression disorder (dysthymia) and were treated in a residential therapeutic community for a period of six to eight months. The original sample was divided into two groups: during (In-Treatment) and after treatment (one-year Post-Treatment). The assessment protocol was composed of Beck Depression Inventory (BDI II), Self-Compassion Scale (SELFCS) and sociodemographic characterization. Results: The sample was composed of 63 participants, 28 females and 35 males (age: M = 32.84, SD = 10.24). Women presented lower levels of self-kindness and self-compassion (total score), and higher levels of all the negative dimensions of SELFCS. Patients with moderate or severe symptoms of depression indicated a lower total score of self-compassion as well as higher scores in all the negative dimensions; patients having undergone previous treatments showed higher levels of symptomatology of depression. The group assessed after the intervention presented higher levels of self-compassion and lower levels of over-identification, when compared to the group that was assessed still undergoing treatment. Finally, the self-judgment dimension of the SELFCS stands out as a predictor of depression for the total sample and the SELFCS’s isolation dimension is a predictor of BDI’s scores for the group undergoing treatment. Discussion: Although most of the results are in line with similar findings of the existing literature about the relationship between the studied variables, some were unexpected, and may guide the direction of future studies and the application of these concepts within the clinical context.
The relationship between core stability and some performance parameters between fourteen and sixteen year old group male long distance runners and football players

The purpose of this study is to examine the relationship between core stability and some performance parameters in 14-16 age group male long distance runners and football players. 15 male long distance runners and 15 male football players with an average whose height measured ranged from 172.400 ± 7.3513 cm participated in the study. Core stability was determined by plank test and performance values were measured by using tests such as; 30 m speed running, pro-agility, long jump and 60 s shuttle pull. Descriptive and paired-sample t tests were used to compare core stability and performance values. When it is analysed according to football and athletics branches, it is seen that there is no significant difference between the branches in terms of height, body weight, BMI (Body Mass Index), plank and shuttle numbers they can pull in 60 seconds (p < 0.05). However, it was found that 30 m speed running time, standing long jump distance and pro-agility test values showed a significant difference in favour of athletics (p < 0.01).
A Comparison of Network Clustering Algorithms in Keyword Network Analysis: A Case Study with Geography Conference Presentations

Abstract The keyword network analysis has been used for summarizing research trends, and network clustering algorithms play important roles in identifying major research themes. In this paper, we performed a comparative analysis of network clustering algorithms to find out their performances, effectiveness, and impact on cluster themes. The AAG (American Association for Geographers) conference datasets were used in this research. We evaluated seven algorithms with modularity, processing time, and cluster members. The Louvain algorithm showed the best performance in terms of modularity and processing time, followed by the Fast Greedy algorithm. Examining cluster members also showed very coherent connections among cluster members. This study may help researchers to choose a suitable network clustering algorithm and understand geography research trends and topical fields.
Video Question Answering for Surveillance

There are many task in surveillance monitoring such as object detection, person identification, activity and action recognition etc. Integrating variety of surveillance task through a multimodal interactive system will benefit real-life deployment, and will also support human operators. We first introduce a dataset which is first of its kind and named as Surveillance Video Question Answering (SVideoQA) dataset. The multi-camera surveillance monitoring aspect is considered through the multimodal context of Video Question Answering (VideoQA) in the SVideoQA dataset. This paper proposes a deep learning model where VideoQA task on the SVideoQA dataset is attempted to solved in a manner where memory-driven relationship among appearance and motion aspect of the video features are captured. At each level of the relational reasoning respective attentive parts of the context of the motion and appearance features are identified forwarded through frame level and clip level relational reasoning module. Also, respective memories are updated which are again forwarded to the memory-relation module to finally predict the answer word. The proposed memory-driven multilevel relational reasoning is made compatible with the surveillance monitoring task through the incorporation of multi-camera relation module, which is able to capture and reason over the relationships among the video feeds across multiple cameras. Experimental outcome exhibits that the proposed memory-driven multilevel relational reasoning perform significantly better on the open-ended VideoQA task compared to other state-of-the art systems. The proposed method achieves an accuracy of 57\% and 57.6\% respectively for the single-camera and multi-camera task of the SVideoQA dataset.
PARAMETERS ESTIMATION OF LINEAR, QUADRATIC AND EXPONENTIAL MODELS FOR ENERGY DEMAND FORECASTING BY USING ABC ALGORITHM

The accurate energy demand forecasting is important issue for energy supplier companies. Especially, the electrical energy price is defined one day ago depending on energy demands. Developed accurate model increases management capacity and efficient usage of power plants. Despite the fact that, In Turkey, transformer based energy measurement for a specific region is still developing topic and application, the consumption data for a specific region can be very limited. In cases where there is limited data, modeling is a difficult task to perform. Although there are several methods have been proposed before, they suffers from forecasted values close to real ones efficiently. In this study, a model was developed to forecast electrical energy consumption in a specific industrial region in Turkey. In the model, the energy consumption of an industrial region between years of 2014 – 2016 was considered as output values and temperature and energy consumption values belonging one day ago are defined as input values. The output values were estimated by giving input values to the model, which is based on linear, quadratic and exponential functions. In the study, parameters of these functions were defined by Artificial Bee Colony Algorithm (ABC) by minimizing the error value between predicted and real values. Results obtained from three different functions were compared with each other and shown as graphically. Results show that the ABC algorithm can define the parameters of functions very accurately by decreasing the error value very close to zero. Index Terms Energy demand forecasting, Artificial Bee Colony, parameter estimation, linear regression
A Reconfigurable Architecture for Discrete Cosine Transform in Video Coding

Discrete cosine transform (DCT) is an indispensable module in video codecs and is a major part in many video coding standards including the latest high efficiency video coding (HEVC). As the video resolution increases, both transform sizes and the number of transforms increase continuously which poses challenges to the reusability design especially in hardware implementation. This paper presents reconfigurable transform architecture to flexibly support the reusability of different transform sizes. The proposed architecture maximally reuses the hardware resources by rearranging the order of input data for different transform sizes while still exploiting the butterfly property. Furthermore, this architecture supports reconfigurable throughput according to different hardware resource requirements. By applying the proposed architecture to the field-programmable gate array (FPGA) design of HEVC core transform matrices, the synthesis results show much lower consumption of hardware resources comparing to existing methods in the literature. The implementation in Altera’s Stratix III FPGA can operate at 139 MHz and supports real-time processing of $3840\times 2160$ ultra-high definition video at a minimum of 45 f/s and up to 359 f/s for different DCT sizes.
Irregularity Effects of Masonry Infills on Nonlinear Seismic Behaviour of RC Buildings

Despite extensive research studies, the seismic response of infilled reinforced concrete buildings remains an open problem due to both the complexity of the interaction between the infill and the frame and the large number of parameters involved. Thus, guidelines for both modelling and analysis are still lacking and the infill walls are normally treated as nonstructural components in seismic codes. However, it may be not conservative to neglect the influence of infills. In fact, the infill masonry walls may significantly affect the stiffness, strength, and energy dissipation capacity of RC buildings, even when they are regularly distributed. Recognizing this influence and its importance on the vulnerability of infilled frames, Eurocode 8 requires amplifying seismic action effects due to infills. In this paper, the effectiveness of the Eurocode 8 design provisions for infill irregularity in plan and/or elevation was investigated. To this aim, different in-plan layouts of infill walls were selected as marginal cases for which Eurocode 8 does not require amplification of the action effects due to the presence of infills, or the additional measures to counteract these effects are not mandatory. The seismic vulnerability of the infilled RC buildings was evaluated using nonlinear static and nonlinear dynamic analyses. Both cracking and crushing of masonry and stiffness and strength degradation were considered in the analysis. The effect of the layout of the masonry infills on the seismic response in terms of resistance and displacement was evaluated. Results show that in one of the case studies here examined, it is not conservative to neglect the influence of infill panels. In fact, structural failure due to torsion and soft-storey effects may occur even in cases where Eurocode 8 does not require the amplification of the action effects. Finally, the total shear demand on columns may be underestimated, even in cases where the code provisions for infills irregularity are not mandatory, and the additional shear demand in the columns induced by the masonry infill is very low.
Fabrication of Alternative Bolus for Cobalt-60 Teletherapy Using Two Locally Available Materials

Bolus is a tissue equivalent material which is use in radiation therapy in order to eliminate skin sparing effect of higher energy photon beams that always reduce the surface dose. There are several commercially bolus material such as Superflab, Aquaplast and gels for use but literature have shown that they are expensive and are not readily available in developing countries. This work presents the fabrication of an alternative bolus for Cobalt-60 Teletherapy using two locally available materials (Beeswax and Petroleum jelly). Beeswax was liquefied at a temperature of 60°C followed by the addition of Petroleum jelly at ratio 3:1 by weight for proper molding and flexibility. In order to determine the depth of maximum dose, Thermoluminescent Dosimeter (TLD) chips were inserted in between ten bolus materials of thickness 0.5 cm that were arranged in layers and placed on a solid water phantom. This was then irradiated with Cobalt-60 radiation source using field size ranging from 5 cm x 5 cm to 10 cm x 10 cm field size. For all the field size, maximum absorbed dose was found to be at 0.5 cm depth. This depth of maximum dose was compared to two tissue equivalent materials in use in radiation therapy: water and Superflab for Cobalt-60 Teletherapy and found to be in agreement. The percentage dose deviation when compared with water for 1 cm, 2 cm, 3 cm, 4 cm and 5 cm were less than 2%. The flexibility of the bolus material and the analysis of the absorbed dose measured have shown that the fabricated bolus material of thickness 0.5 cm can be used as an alternative bolus material for Cobalt-60 Teletherapy.