Miracle-dz/UniFAR-FTUs huggingface dataset:
THE NEW GREEN REVOLUTION: HOW 21 CENTURY SCIENCE CAN FEED THE WORLD

105 Some crises appear and disappear in global media while remaining acute in the lives of real people. Global food insecurity is this type of crisis. In January 2011 the Food and Agriculture Organization of the United Nations (FAO) warned that global food prices in December 2010 exceeded the 2008 peak during the so-called food price crisis that sparked food riots across Africa, Asia, and Latin America. The UN also warned that the price increase would not stop overnight and that we were entering danger territory. Although prices stabilized in the spring, global food prices in May 2011 remained higher than they were in June 2008. We will see more price spikes in the future, due to a growing discrepancy between supply and demand, the impacts of climate disruption on agricultural production, and the merger of the energy and food markets. The food crisis is here to stay.
An Isolated High Step-Up Converter with Non-Pulsating Input Current for Renewable Energy Applications

This study proposes a novel isolated high step-up galvanic converter, which is suitable for renewable energy applications and integrates a boost converter, a coupled inductor, a charge pump capacitor cell, and an LC snubber. The proposed converter comprises an input inductor and thus features a continuous input current, which extends the life of the renewable energy chip. Furthermore, the proposed converter can achieve a high voltage gain without an extremely large duty cycle and turn ratio of the coupled inductor by using the charge pump capacitor cell. The leakage inductance energy can be recycled to the output capacitor of the boost converter via the LC snubber and then transferred to the output load. As a result, the voltage spike can be suppressed to a low voltage level. Finally, the basic operating principles and experimental results are provided to verify the effectiveness of the proposed converter.
RF transceiver design for electronic toll collection system (ETC) using compact dipole antenna

RF Transceiver Design for Electronic Toll Collection (ETC) System Using Compact Dipole Antenna by Anjana Chowdary Devineni Electronic Toll Collection (ETC) system is one of the types of traffic control system that has rapid development in the recent years. ETC system is one of the major applications of Dedicated Short Range Communication (DSRC) which operates in the frequency band of 5.8GHz, used for the transfer of information between the road side unit (RSU) and the on board unit (OBU) which are situated at the toll station and on the vehicle respectively. The working of the system is based on RFID technology. ETC system is implemented in the 0. 18μm CMOS technology, which is an aggressive technology in terms of its low cost and easy integration of the RF circuits. A compact dipole antenna based low-cost RF transceiver for ETC system is designed in this thesis. Amplitude Shift Keying (ASK) modulation technique is employed in the implemented RF transceiver. In transmitter side, a class-E power amplifier is used to amplify the signal power. In order to send and receive the signal, a dipole antenna operating at a frequency of 5.8GHz is used. A low-power and energy efficient Low-Noise Amplifier (LNA) is used in the receiver block which consumes very less power and has a minimal noise figure compared with prior arts. A self-mixer is used for the down-conversion of the signal. Results of this design demonstrate the working of the transceiver at 5.8GHz frequency up to an input data rate of 400 Mbps.
Game Theory and Risk Analysis

Risk analysts often analyze adversarial risks from terrorists or other intelligent attackers without mentioning game theory. Why? One reason is that many adversarial situations—those that can be represented as attacker‐defender games, in which the defender first chooses an allocation of defensive resources to protect potential targets, and the attacker, knowing what the defender has done, then decides which targets to attack—can be modeled and analyzed successfully without using most of the concepts and terminology of game theory. However, risk analysis and game theory are also deeply complementary. Game‐theoretic analyses of conflicts require modeling the probable consequences of each choice of strategies by the players and assessing the expected utilities of these probable consequences. Decision and risk analysis methods are well suited to accomplish these tasks. Conversely, game‐theoretic formulations of attack‐defense conflicts (and other adversarial risks) can greatly improve upon some current risk analyses that attempt to model attacker decisions as random variables or uncertain attributes of targets (“threats”) and that seek to elicit their values from the defender's own experts. Game theory models that clarify the nature of the interacting decisions made by attackers and defenders and that distinguish clearly between strategic choices (decision nodes in a game tree) and random variables (chance nodes, not controlled by either attacker or defender) can produce more sensible and effective risk management recommendations for allocating defensive resources than current risk scoring models. Thus, risk analysis and game theory are (or should be) mutually reinforcing.
Secondary Lymphoid Tissue Cells Maintain Memory CD4 T Cells within Cutting Edge: Lymphoid Tissue Inducer

Phylogeny shows that CD4 T cell memory and lymph nodes coevolved in placental mammals. In ontogeny, retinoic acid orphan receptor (ROR) g -dependent lymphoid tissue inducer (LTi) cells program the develop-ment of mammalian lymph nodes. In this study, we show that although primary CD4 T cell expansion is normal in ROR g -deﬁcient mice, the persistence of memory CD4 T cells is ROR g -dependent. Further-more, using bone marrow chimeric mice we demonstrate that LTi cells are the key ROR g -expressing cell type sufﬁcient for memory CD4 T cell survival in the absence of persistent Ag. This effect was speciﬁc for CD4 T cells, as memory CD8 T cells survived equally well in the presence or absence of LTi cells. These data demonstrate a novel role for LTi cells, archetypal members of the innate lymphoid cell family, in supporting memory CD4 T cell survival in vivo. The Journal of Immunology , 2012, 189: 000–000.
Design, development, and flight testing of a high endurance micro quadrotor helicopter

This paper describes the experimental design studies conducted to maximize the hover endurance of a micro air vehicle-scale quadrotor helicopter (gross weight < 50 g) by careful design and selection of the individual subsystems while understanding their interdependencies. The different subsystems of the quadrotor that were examined include the rotors, motors, electronic speed controllers, gear transmission systems, battery, and airframe structure. An optimized micro air vehicle-scale rotor with a diameter of 110 mm and a figure of merit of 0.67 served as the basis for the vehicle design. Brushed and brushless motor systems were paired with the optimized rotor and were examined for maximum system level efficiency and capability to produce the required thrust. Propulsion systems using brushed motors with speed controllers and the optimum gear ratio showed up to 35% improvement in efficiency over brushless outrunner motors with speed controllers. Lithium-ion polymer batteries were compared and evaluated on voltage drop-off characteristics and achievable endurance versus weight. Quadrotor airframe weight has been minimized to 7.4% of the gross weight, representing a 30–50% decrease compared existing similarly sized quadrotors. The highest endurance was obtained using brushed motors with a 5.33:1 gear ratio and a 650 mAh battery. Presently, the longest continuous hover endurance achieved with this design is 31 min.
The Reshaping Technology for Three Dimensional Polysilicon Microstructures

This paper presents a new reshaping technology which is suitable to realize real three dimensional silicon microstructures. In this process, the elastically deformed polysilicon structure is annealed by Joule heating generated by the current passing through the structure. Plastic deformation occurs resulting in permanent three dimensional shapes. The application of this basic process to different polysilicon structures is successfully performed. Some quantitative characteristics of the annealing effects are also investigated by means of structure deformation measurements.
The Influence of Driver Expectation when Recognizing Lighted Targets at Nighttime

Over the years, in a night time driving scenario, expectancy has been linked with faster night time recognition. This study tries to evaluate the ability of observers to identify illuminated objects on the road in the absence of an associative pattern. In this study 47 of 60 participants did not respond to a light source that was in the drivers’ travel lane ahead. Of those who did not respond to the light when directly ahead, 64% indicated that had seen it beforehand. When the light was 2 meters to the drivers’ right, 33% that saw the light failed to respond. All of the drivers who saw the light before striking it claimed that they thought it was off the road until too late. When the drivers did not know what the light source was, they could not decipher where the light was. However, once aware of the presence of the light the average recognition distance improved 192 meters (632 feet) with 100% recognition. These results fit well with the SEEV search model and an Information Theory approach to driver expectancy. Previous claims that the difference between expected and unexpected driver responses is a 2 to 1 ratio was not supported by this research.
A Web of Things integrated Sensor Platform for Precision Agriculture

This thesis introduces the AgriSenseBox , a Web of Things integrated Sensor Plat-form for Precision Agriculture. Based upon open hardware, the AgriSenseBox provides a web server containing a RESTful interface. The sensor platform is de-ployable in the ﬁeld and makes sensor data processable without caring of differing formats. The AgriSenseBox is encoding its measurements as JSON using the structure proposed by O&M and hands out links to descriptions of the attached sensors. Following the principles of the WoT, sensor data is browseable by using web standards, such as HTTP and URI.
RETENTION AND RECRUITMENT SATISFACTION: A STUDY AT OIL INDUSTRY IN PUBLIC SECTOR

Today’s “best” companies understand that the real key to maintain a world class is not just to hire the best, but to retain them for their competency and organizational learning. The outcome of the pilot study conducted at an oil company of a public sector undertaking in India showed that beside some common factors for retention the satisfaction of the recruitment process is a unique factor. The study conducted on randomly selected 120 employees at eastern region shows that the junior and middle level employees are very much loyal to their organisation, but somehow due to inflexibilities in some of the organizational culture/ policies seniors are not so satisfied. Correlation and regression analysis shows that recruitment satisfaction plays a major role in retaining employees. Beside this, job environment ie, environment, increment and facilities and job values ie, job itself and accomplishment are positively correlated with retention of employees.
Edinburgh Research Explorer Assessment of beta-amyloid deposits in human brain: a study of the BrainNet Europe Consortium Assessment of (cid:1) -amyloid deposits in human brain: a study of the BrainNet Europe Consortium

(cid:1) -Amyloid (A (cid:1) ) related pathology shows a range of lesions which di V er both qualitatively and quanti-tatively. Pathologists, to date, mainly focused on the assessment of both of these aspects but attempts to correlate the W ndings with clinical phenotypes are not convincing. It has been recently proposed in the same way as (cid:2) and (cid:1) synuc-lein related lesions, also A (cid:1) related pathology may follow a temporal evolution, i.e. distinct phases, characterized by a step-wise involvement of di V erent brain-regions. Twenty-six independent observers reached an 81% absolute agreement while assessing the phase of A (cid:1) , i.e. phase 1 = deposition of A (cid:1) exclusively in neocortex,
Robust No-Regret Learning in Min-Max Stackelberg Games

The behavior of no-regret learning algorithms is well understood in two-player min-max (i.e, zero-sum) games. In this paper, we investigate the behavior of no-regret learning in min-max games with dependent strategy sets , where the strategy of the first player con-strains the behavior of the second. Such games are best understood as sequential, i.e., min-max Stackelberg, games. We consider two settings, one in which only the first player chooses their actions using a no-regret algorithm while the second player best responds, and one in which both players use no-regret algorithms. For the former case, we show that no-regret dynamics converge to a Stackelberg equilibrium. For the latter case, we introduce a new type of regret, which we call Lagrangian regret, and show that if both players minimize their Lagrangian regrets, then play converges to a Stackelberg equilibrium. We then observe that online mirror descent (OMD) dynamics in these two settings correspond respectively to a known nested (i.e., sequential) gradient descent-ascent (GDA) algorithm and a new simultaneous GDA-like algorithm, thereby establishing convergence of these algorithms to Stackelberg equilibrium. Finally, we analyze the robustness of OMD dynamics to perturbations by in-vestigating online min-max Stackelberg games. We prove that OMD dynamics are robust for a large class of online min-max games with independent strategy sets. In the dependent case, we demonstrate the robustness of OMD dynamics experimentally by simulating them in online Fisher markets, a canonical example of a min-max Stackelberg game with dependent strategy sets. Ap-plied computing → Multi-agent
RoViST: Learning Robust Metrics for Visual Storytelling

Visual storytelling (VST) is the task of generating a story paragraph that describes a given image sequence. Most existing storytelling approaches have evaluated their models using traditional natural language generation metrics like BLEU or CIDEr. However, such metrics based on n-gram matching tend to have poor correlation with human evaluation scores and do not explicitly consider other criteria necessary for storytelling such as sentence structure or topic coherence. Moreover, a single score is not enough to assess a story as it does not inform us about what specific errors were made by the model. In this paper, we propose 3 evaluation metrics sets that analyses which aspects we would look for in a good story: 1) visual grounding, 2) coherence, and 3) non-redundancy. We measure the reliability of our metric sets by analysing its correlation with human judgement scores on a sample of machine stories obtained from 4 state-of-the-arts models trained on the Visual Storytelling Dataset (VIST). Our metric sets outperforms other metrics on human correlation, and could be served as a learning based evaluation metric set that is complementary to existing rule-based metrics.
RP-HPLC Analysis of Flavonoids in Marsilea Minuta L

The present study was investigated for the presence of phenolic compounds in the plant extract of Marsilea minuta L. The studies on the phenolics or flavonoids by RP-HPLC analysis showed the presence of five flavonoid compounds such as gallic acid, caffeic acid, rutin, quercetin and ferulic acid. The chromatographic separations at retention time (Rt) for gallic acid (Rt 5.675), Caffeic acid (Rt – 9.475), Rutin (Rt -11.017), Quercetin (Rt -12.175) and Ferulic acid (Rt 23.808). The individual flavonoid content for all the flavonoids were calculated from the corresponding calibration curve and the obtained values were compared with the standards. Hence these plant extracts with the property of phenolic compounds can be recommended for their use as an alternative anti-infective agent in natural medicine for the treatment of various diseases.
The Problem of Over-Design for Darwinism

ISSN: 1937-9056 Copyright © 2022 Answers in Genesis, Inc. All content is owned by Answers in Genesis (“AiG”) unless otherwise indicated. AiG consents to unlimited copying and distribution of print copies of Answers Research Journal articles for non-commercial, non-sale purposes only, provided the following conditions are met: the author of the article is clearly identified; Answers in Genesis is acknowledged as the copyright owner; Answers Research Journal and its website, www.answersresearchjournal. org, are acknowledged as the publication source; and the integrity of the work is not compromised in any way. For website and other electronic distribution and publication, AiG consents to republication of article abstracts with direct links to the full papers on the ARJ website. All rights reserved. For more information write to: Answers in Genesis, PO Box 510, Hebron, KY 41048, Attn: Editor, Answers Research Journal. The views expressed are those of the writer(s) and not necessarily those of the Answers Research Journal Editor or of Answers in Genesis. Abstract The case for over-design is reviewed focusing on documented cases of normal persons that have exceptional abilities. Over-design refers to mental skills that exist at levels well-beyond that required for survival. Typical abilities and skills achieved by the human brain, such as in music, math, memory, and design, are also used as examples to illustrate the concept of over-design. Several case histories of exceptional abilities were reviewed to illustrate extreme cases of mental over-design. These cases provide strong support for a level of intelligent design that cannot be explained by Darwinism. A literature review concludes these exceptional skills remain unexplained in spite of numerous scientific studies that have explored this topic. Among those persons convinced that over-design requires an intelligent creator is the co-founder of the modern Neo-Darwinism theory of evolution, Alfred Russel Wallace.
Mathematical Modeling and Simulation for Microbial Enhanced Oil Recovery Optimization

In this study, we developed a mathematical model for 2D microbial EOR technology. It consists of an average pressure formulation of two-phase flow and component advection-diffusion reactive transport models. An IFT reduction mechanism has been used to couple porous media flow and transport phenomenon. A cell centered control volume and backward Euler methods were applied to discretize the flow and transport equations. An iterative linearization technique is implemented in Matlab to solve the resulting system of non-linear algebraic equations. Numerical experiments were conducted on two-phase flow, advection-diffusion transport and the coupled microbial EOR models for different mobility and capillary pressure parameterizations. Moreover, we have proposed a new microbial EOR optimization model to maximize the sweep efficiency by controlling the slug size injection strategy. In this thesis, we have also proposed a new optimization algorithm based on gradient accent and iterative linearization methods to handle the microbial EOR optimization model numerically. A number of illustrative numerical experiments have been done to analyse the effect of slug size and cost of microbial concentration.
Understanding Students' Problem-Solving Processes via Action Sequence Analyses (Short Paper)

The transition of the National Assessment of Educational Progress (NAEP) to digitally based assessments (DBAs) allowed for the collection of data that can provide insights into students’ problemsolving processes. When students interact with a NAEP DBA item, their recorded timestamped events in the process data form sequences. We refer to action sequences as the series of clicks or other actions a student makes within an item. Using data from one released block of the NAEP 2017 mathematics assessment for grade 4, this study aims to provide an understanding of the relationships among action sequence characteristics, item characteristics and student performance. First, we extract individual actions sequences across items. Second, we categorize each individual action into one of four activities: Browsing, Passive investigation, Active investigation, or Decision. This categorization enables us to investigate sequence patterns within and across different items. Sequence characteristics are summarized from two perspectives: a) the time spent on each activity is calculated for each student across items and b) the within-sequence entropy (Shannon, 1948) and turbulence (Elzinga, 2006) of the sequences are calculated to quantify students’ action mobility. We found that the time students spend on “Decision” and “Passive investigation” activities can be used to predict student performance.
The Privacy versus Disclosure Appetite Dilemma: Mitigation by Recommendation

Social Networking Sites (SNS) are growing exponentially and have undoubtedly become an intrinsic part of our lives. This is accompanied by a spike in the amount of time spent by users online, namely teenagers and young adults who allocate an average of three hours a day for various types of SNS. From commenting, posting sharing opinions to selfies and videos, they expose numerous pieces of personal information, jeopardizing their privacy. Specifically, this self-disclosure is driven by various factors including the individual’s sharing needs, the information being shared as well as the target audience. As such, it is a multi-layered issue to which the one-size-fits-all interventions, currently being used, have not proven to be most effective. This paper proposes a novel harm-aware recommender system-based solution to help the user take privacy-preserving decisions while using social media. This novel take on self-disclosure mitigation leverages notions from behavioural economics as well as psychological measurements. One of the contributions of this paper is the conception of the disclosure appetite, which is a user-specific term that encompasses their perception and their drive to reveal their private information. The tailored privacy-aware recommendations rely on the psychometric value that is the disclosure appetite as well as the sensitivity of the data being revealed. Through a trade-off between the two parameters, the system aims to mitigate the privacy compromise while considering the preferences of the user. In the era of oversharing and living virtually, this system that handles private data, with the intention of preserving it, is more crucial than the common uses of recommenders. In most of those cases, the extent of personal information exchanged does not go beyond preferences. Whereas the consequences and preventive potential of this work can have a bigger impact on multiple facets of the users’ lives. Finally, an empirical evaluation is conducted using participants from the US, Canada and Europe.