Miracle-dz/UniFAR-FTUs huggingface dataset:
DYNAMATE : Automatic Checking loop invariants using Mutation,Dynamic Analysis and static checking

: aAutomatic program verification, proving program correct still requires substantial expert manual effort. One of the biggest burden is providing loop invariants properties that hold for every iteration of a loop. Compared to other requirement elements such as pre -and post conditions, loop invariants tend to be difficult to understand and to express. The proposed system automates the functional verification of incomplete correctness of programs with loops by inferring the required loop invariants. In this approach it combines complementary techniques such as test case generation, dynamic invariant detection, and static verification. This approach can be implemented by a tool called DYNAMATE. DYNAMATE improves the flexibility of loop invariant inference by combining static (proving) and dynamic (testing) techniques. The DYNAMATE tool presented in this process combines different techniques with the overall goal of providing fully automatic verification of programs with loops
Identification and Estimation of Multi-Period Simple Contracts∗

This paper provides an econometric framework to analyze two-period simple contracts models where the principal offers the agent to choose between a fixed-price contract and a cost-reimbursement one in each period. We establish nonparametric identification for all model primitives, conditional on that the agent exerts effort. These primitives include agent’s cost and disutility functions, distribution of innate costs (type), and parameters that characterize agent’s bargaining power and the intertemporal preference. We then propose a consistent estimation procedure. In our empirical study, using the data on transport procurement contracts in France, we find strong evidence that the agent’s optimal effort is monotonic in its innate cost, rather than being a constant as would be implied by linear cost functions. A counterfactual analysis evidences the importance of this finding by showing that welfare implications under monotone optimal effort differ a lot from those under constant optimal effort.
Optimal Control of Lossy Energy Storage Systems With Nonlinear Efficiency Based on Dynamic Programming and Pontryagin's Minimum Principle

We consider energy storage systems having nonlinear efficiency functions, which are becoming increasingly important as shown in several recent works, and propose an optimal solution based on Pontryagin's minimum principle. A central challenge in such problems is the hard limits on the state variable, which restrict the use of the minimum principle. To address this challenge, we propose to include the capacity constraints in the objective function with a proper weighting constant. We show that this approach allows formulation of the problem based on the classical minimum principle, and eventually leads to an efficient optimal control strategy. The proposed solution is compared to a dynamic programming algorithm. Numeric experiments reveal that for lossless storage devices dynamic programming is beneficial, since it enables fast and accurate solutions when a low number of samples is used. However, for lossy storage devices the situation is the opposite, and the minimum principle provides faster and more accurate solutions, since its computational complexity is almost unaffected by changes in the system parameters.
Diverting electron fluxes towards sulfate reduction using linoleic acid in a mixed anaerobic culturePaper submitted to the Journal of Environmental Engineering and Science.

Sulfate (1500 mg/L) reduction and glucose (1870 mg/L) degradation was examined in the presence of five varying linoleic acid (LA) levels (100–1000 mg/L) at 37 ± 2 °C and pH 7.0–7.2. The sulfate reduction and methane formation data suggest that LA selectively inhibited methane producing bacteria (MPB). The quantity of sulfate removed increased with increasing LA dosage. Approximately 1375 mg/L (92%) sulfate was removed in cultures fed with high concentrations of LA (1000 mg/L), which was 68% more than that removed in glucose and sulfate controls. The quantity of sulfate removed in cultures fed with 100, 300, 500 and 700 mg/L LA were 62%, 66%, 77%, and 84%, respectively. Initial sulfate degradation rates increased with increasing LA levels in the cultures. High LA levels (1000 mg/L) attributed to approximately a sevenfold increase in the initial sulfate degradation rates compared to cultures containing sulfate plus glucose. The highest initial sulfate removal rate (0.19 µg/(mgVSS min)) was observed in cultu.
Feeding Performance of King Mackerel,

INTRODUCTION Feeding performance, the ability to successfully capture and handle prey (Wainwright, '88, '91; Van Wassenbergh et al., 2007; Habegger et al., 2010), is dependent upon a variety of sensory and musculoskeletal processes. Predators must first locate potential prey items using olfactory, visual, electrical, and hydrodynamic stimuli (Shashar et al., 2000; Pohlmann et al., 2001; Stewart et al., 2013), after which a successful strike must be initiated. Strikes may involve significant contribution of the locomotor system, as is the case in ram feeders such as the great barracuda, Sphyraena barracuda, which capture prey by striking at high velocity (Grubich et al., 2008; Porter and Motta, 2004). Alternatively, locomotion may make little contribution to the strike, as exemplified by suction feeders such as the sunfishes, family Centrarchidae, which generate negative pressures within the oropharyngeal cavity to draw water and prey into the mouth (Lauder, '80; Wainwright et al., 2001; Higham et al., 2005). Once prey is acquired, it generally must be processed, depending on prey size and mechanical properties, within the oropharyngeal cavity via biting prior to deglutition (Huber et al., 2005; Grubich et al., 2008; Mara et al., 2009; Whitenack and Motta, 2010; Erickson et al., 2012). While it is apparent that acquiring food involves the coordinated performance of sensory, locomotive, and feeding mechanisms, feeding studies have generally examined only individual performance parameters at a time. The simultaneous examination of multiple performance parameters will likely yield ABSTRACT Feeding performance is an organism's ability to capture and handle prey. Although bite force is a commonly usedmetric of feeding performance, other factors such as bite pressure and strike speed are also likely to affect prey capture. Therefore, this study investigated static bite force, dynamic speeds, and predator and prey forces resulting from ram strikes, as well as bite pressure of the king mackerel, Scomberomorus cavalla, in order to examine their relative contributions to overall feeding performance. Theoretical posterior bite force ranged from 14.0–318.7 N. Ram speed, recorded with a rod and reel incorporated with a line counter and video camera, ranged from 3.3– 15.8B L/s. Impact forces on the prey ranged from 0.1–1.9 N. Bite pressure, estimated using theoretical bite forces at three gape angles and tooth cross-sectional areas, ranged from 1.7– 56.9MPa. Mass-specific bite force for king mackerel is relatively low in comparison with other bony fishes and sharks, with relatively little impact force applied to the prey during the strike. This suggests that king mackerel rely on high velocity chases and high bite pressure generated via sharp, laterally compressed teeth to maximize feeding performance. J. Exp. Zool. 9999A: XX–XX, 2015. © 2015 Wiley Periodicals, Inc. How to cite this article: Ferguson AR, Huber DR, Lajeunesse MJ, Motta PJ. 2015. Feeding Performance of King Mackerel, Scomberomorus Cavalla. J. Exp. Zool. 9999:1–15. J. Exp. Zool. 9999A:1–15, 2015
Physical Principles and Recent Advances of Medical Imaging Systems

In this paper, a variety of medical imaging systems including Ultrasonography, MRI, Bone Densitometry, Optical Coherence Tomography, Arthrography, etc. are reviewed and their advantages and disadvantages are also described. In addition to these methods, new techniques in medical imaging such as Shear Wave Elastography and Ultrashort Echo Time are also being reviewed. One of the most important of these methods is radiology imaging. Radiology is one of a variety of methods for imaging various parts of the body. Basically, the first assessment of the patient is radiology. Radiology is a non-invasive and rapid method for diagnosis. The basis of this method is the ionizer radiation rays. Radiology medicine is divided into two parts: diagnostic and therapeutic. Radiology medicine based on the energy used is divided into two types: radiology and nuclear medicine. The basis for the function of radiology is X-rays and the basis for the performance of nuclear medicine is radioactive material. Radiology is more dangerous than nuclear medicine, and is not suitable for pregnant women and children. But radiology is more accurate and faster than other methods. In addition to its advantages, this method also includes dangers for the human body. Wilhelm Röntgen was the first scientist to discover X-rays and record the first radiology image. This paper describes the components of a radiology device, including a X-ray tube, a collimator, a detector, and so on.
Comorbidities associated with regional variations in COVID-19 mortality revealed by population-level analysis

Coronavirus disease 2019 (COVID-19), caused by severe acute respiratory syndrome coronavirus 2 (SARS-Cov-2), has developed into a global health crisis. Understanding the risk factors for poor outcomes of COVID-19 is thus important for successful management and control of the pandemic. However, the progress and severity of the epidemic across different regions show great differentiations. We hypothesized the origination of these differences are based on location-dependent variations in underlying population-wide health factors. Disease prevalence or incidence data of states and counties of the United States were collected for a group of chronic diseases, including hypertension, diabetes, obesity, stroke, coronary heart disease, heart failure, physical inactivation, and common cancers (e.g., lung, colorectal, stomach, kidney and renal). Correlation and regression analysis identified the prevalence of heart failure as a significant positive factor for region-level COVID-19 mortality. Similarly, the incidence of gastric cancer and thyroid cancer were also identified as significant factors contributing to regional variation in COVID-19 mortality. To explore the implications of these results, we re-analyzed the RNA-seq data for stomach adenocarcinoma (STAD) and colon carcinoma (COAD) from The Cancer Genome Atlas (TCGA) project. We found that expression of genes in the immune response pathways were more severely disturbed in STAD than in COAD, implicating higher probability for STAD patients or individuals with precancerous chronic stomach diseases to develop cytokine storm once infected with COVID-19. Taken together, we conclude that location variations in particular chronic diseases and cancers contribute significantly to the regional variations in COVID-19 mortality.
Flexible and Stretchable Brush-Painted Wearable Antenna on a 3D Printed Substrate

This letter presents the proof-of-concept of the fabrication and performance analysis of a flexible and stretchable wearable antenna on a 3D printed substrate. It presents the details of the 3D printing of the substrate, brush-painting of the antenna, as well as the simulation and measurement results of the antenna. In addition, the bending test is done to check the limitation of the manufacturing method. The results show that the stretchable silver conductive paste achieves a 1.7×104 S/m conductivity. The fabricated antenna shows measured impedance bandwidth of 990 MHz (1.94 GHz – 2.93 GHz) with a peak gain of -7.2 dB at 2.45 GHz. Moreover, the antenna shows excellent wireless performance even when bent. Based on the results, the presented approach can be used for the manufacturing of wearable antennas and wireless on-body applications.
Modeling Gravitational Waveforms from Stellar Encounters

This paper calculates the luminosity of gravitational waves emanating from close stellar encounters in both the classical limit and with first order post-Newtonian corrections. We also model gravitational waveforms with post-Newtonian corrections through the first order for varying eccentricities and angles of observation. Models are also generated using classical methods and are compared to those with post-Newtonian corrections. The stellar systems considered include bounded orbits with circular and elliptical trajectories as well as unbounded encounters such as parabolic and hyperbolic systems. We found that eccentricity has a much more pronounced effect on the shape of the gravitational waveform and the strain amplitude than the angle of observation, a dependence that is only introduced by post-Newtonian corrections.
The location of the Italian manufacturing industry, 1871-1911: a quantitative analysis

This paper analyzes spatial location patterns of manufacturing activity in Italy during the period 1871-1911. To this end we use a new dataset of value added at 1911 prices covering the whole set of 69 Italy's provinces (NUTS-3). Total manufacturing value added is disaggregated into 10 industrial sectors. We test the relative e ect of domestic market potential and factor endowment, focusing on water supply. The results show that, as transportation costs decreased and barriers to domestic trade were eliminated, Italian provinces became more and more specialized, and manufacturing activity became increasingly concentrated in a few provinces, mostly belonging to the North-West part of the country. The estimation results corroborate the hypothesis that both comparative advantages (water endowment e ect) and market potential (home-market e ect) have been responsible of this process of spatial concentration. The location of some traditional industries (such as clothing and wood) was mainly driven by water endowment, while the location of fast growing new sectors (such as engineering, metal-making, chemicals, and paper) was mainly driven by the domestic market potential. Our results also suggest that both water supply and domestic market potential were key determinants of the location of the textile industry.
Using DQ0 Signals based on the Central Angle Reference Frame to Model the Dynamics of Large-scale Power Systems

With increasing penetration of distributed and renewable sources into power grids, the dynamic behavior of large-scale power systems is becoming increasingly complex. These recent developments have led to several models attempting to simplify the analysis of dynamic phenomena, among them are models based on the dq0 transformation. A question that often arises when modeling interconnected systems based on dq0 quantities is how to choose the reference frame. One approach is to model the network and its components using a dq0 transformation that is based on a unified reference frame. However, when no generator is large enough to be considered an infinite bus, the unified reference frame may lead to unstable models, since the real frequency may deviate from the nominal frequency used as a reference. In this paper we propose to solve this problem by using the central angle as a basis for the dq0 transformation. Such an approach leads to models which are valid at high frequencies, and can also be used with systems with varying frequencies and no infinite bus. The proposed approach is demonstrated using networks with 9 and 57 buses.
Vein Biometrics Identification Techniques and Challenges

-Numerous biometric traits are in the business when requirement of personalized security is concerned. A biometric is physical or behavioral traits of a person in the visible or hidden form and are used to identify the user uniquely. In this paper, we review the famous biometric traits and try to give overview of trends in their usage. Our goal is to find the burning challenges in this field and to understand the gaps in practical development of hidden biometrics like vein biometrics. Veins hidden in the human body show a unique pattern in every human which is very difficult to forge. Their accurate implementation requires sophisticated hardware which increases the cost of the system out of practical use. So we have come to conclusion that using multimodal biometrics can be a solution for this. We have tried to explore the advantages, methods and shortcomings in this area. We also summarize the instrumentation details.
Sociocultural Determinants of the Utilization of Maternal Health Care Services in the Tallensi District in the Upper East Region of Ghana

Introduction. The quality maternal health care that women receive during pregnancy and delivery is important for the health of both the mother and the baby. However, most pregnant women do not receive the minimum number of antenatal care (ANC) services (at least 4 times during pregnancy) as recommended by the WHO. This article sought to identify the types of maternal health care services (MHCS) received by women during pregnancy and delivery and after childbirth and women’s reasons for use and nonuse of MHCS. Methods. The study adopted the social survey design where 366 women were sampled using probability sampling technique. The data was collected through the use of questionnaire. Results. The study results revealed that some sociocultural factors such as age, religion, traditional belief system, education, and marital status influence women’s use of MHCS in the Talensi District. In addition, factors such as women’s National Health Insurance Scheme status, distance to health center, and attitude of health care professional determine their utilization of MHCS. To a large extent, these factors influence choice for traditional birth attendants over biomedically-based maternal health care services. Conclusion. The study recommended that there should be education for women on the need for them to utilize MHCS during pregnancy and delivery and after childbirth. Government should organize skill training for traditional birth attendants in the Talensi District.
System identification of a twin rotor multi-input multi-output system using adaptive filters with pseudo random binary input

This paper presents an investigation into the development of a parametric model of pitch movement of a twin rotor multi-input multi-output system (TRMS) using adaptive finite impulse response (FIR) models. The TRMS is a laboratory platform designed for control experiments. In certain aspects, its behaviour resembles that of a helicopter. It typifies a high-order nonlinear system with significant cross coupling between its two channels. The system is initially excited with PRBS signals of different bandwidths to ensure that all resonance modes are captured. The PRBS magnitude is selected so that it does not drive the system out of its linear operating range. Then, an adaptive FIR filter structure with LMS, NLMS, and genetic algorithm (GA) with LMS algorithms is investigated to identify the system and extract its parametric model. Effects of filter taps, step-size and system convergence are also studied. Performances of the employed techniques are assessed and presented in time and frequency domains.
LOCAL DISTANCE SOURCE DISCRIMINATION USING INTERPRETABLE MACHINE LEARNING MODELS

The recent maturity and accessibility of machine learning (ML) tools have encouraged scientists from various backgrounds to begin leveraging ML techniques to process and interpret their datasets. In particular, ML has recently been used in seismology for the problem of discriminating explosions from earthquakes at local distances using a state-of-the-art convolutional neural network (CNN) and an adaption of a recurrent neural network called Long-Short-Term-Memory (LSTM). Here, we show that feature-engineered, simple models trained on data that are easy to obtain, process, and store perform similar to cutting-edge, complicated models trained on data streams that require orders of magnitude more storage and extensive processing. Only using three features that do not include waveforms for discriminating explosions from earthquakes in Utah, we train a 94.1 percent accurate random forest and a 93.6 percent accurate logistic regression. These accuracies compare favorably with CNN and LSTM testing accuracies from recent work on a similar dataset using waveform data as the features. The CNN and LSTM were 95.8 percent and 95.9 percent accurate on average for a single station, respectively and 99.2 percent and 99.3 percent accurate on average for a network average, respectively (Linville et al ., 2019). The similar performance between straightforward to implement, interpretable models and computationally expensive models that are oftentimes more difficult to interpret suggests that simple models should be seriously considered prior to introducing more complicated black-box models. The models developed here use M L - M C , a newly proposed depth-discriminant that works at local distance, as one of the model features to evaluate how well it differentiates between earthquakes and explosions as a source-discriminant.
A Comparative Study of Student Engagement in English Classrooms Taught by Native and Non-Native English Speaking Teachers, Koh Kong Province, Kingdom of Cambodia

This study investigated student engagement (behavioral, emotional, and cognitive) in English classrooms taught by Native English Speaking Teachers (NESTs) and Non-native English Speaking Teachers (NNESTs) in Kong Koh Province (the western part of Cambodia) and examined whether students with different years of learning English reported their engagement differently. Mixed-methods research design was used to elicit the data. Two hundred and ten students from Grade 10 and Grade 11 completed the questionnaire. After that, four students from each Grade were interviewed in depth. The quantitative results showed that students reported having more behavioral and emotional engagement in the classes taught by NEST than NNEST. However, for the cognitive engagement, students felt more engaged in the class taught by NNEST than NEST. Additionally, qualitative explained that students felt more engaged in the class taught by NEST because it is the opportunity to use English as well as they can practice pronunciation skills.