Miracle-dz/UniFAR-FTUs huggingface dataset:
Research on the Lateral Balance Control of a Bicycle Robot

In this paper, we focus on a bicycle robot, and discussed the topic how to keep the robot's lateral balance by steering. Firstly, we proposed a dynamical model for the robot by Chaplygin Equation. The proposed model suggests that there should be 3 independent general velocities and 2 driving torques in the system. With the model, we presents a controller for regulating the lateral rolling angle of the bicycle robot by using Global Terminal Sliding Mode Control methodology. As a summary, by taking into account the disturbance of the leaning angle of the frame and the driving velocity of the actuated front-wheel, numerical simulations were seriously performed in Matlab/Simulink, and the results validate the correctness of our dynamical model and the effectiveness of our control algorithm.
"Forgot your password again?": acceptance and user experience of a chatbot for in-company IT support

Over the last few years, chatbots have become a common channel for customer service interactions. In contrast, their usage for in-company applications and respective scientific knowledge about so-called virtual enterprise assistants from a user perspective are still scarce. In this paper, we studied the acceptance and user experience of a chatbot for in-company IT support. In a user study, 12 employees of a bank and a hospital evaluated and assessed a respective chatbot prototype supporting three typical use cases. Our results indicate that such an in-company chatbot is well-suited for structured use cases, such as resetting a password and releasing an email attachment from quarantine. Participants appreciated the simplicity, the pro-active guidance and immediate feedback. The participants assessed a chatbot and the phone as preferred channels to the IT help desk.
On the Analysis of Users' Behavior Based on Mobile Phone Apps

Currently, we live in highly connected environments in which we consume large amounts of data, such as contextual information, and produce even larger amounts of data. In this never-ending cycle, the generated data is taken to other applications, creating pervasive and context-aware systems with which we interact. As this cycle goes on, users share their personal and private data, such as current location, activities, and even their mood, which establish a drawback as users may not want to expose themselves. Therefore, we face a trade-off between sharing personal data and, thus, losing privacy, or not sharing it and, possibly, losing quality of experience in relation to services and applications. In this work, we analyze properties of a mobile phone dataset containing precise information about users' accesses to applications to answer the following questions: (i) What can be inferred from an user at the current time given his/her past information? (ii) How does location data, which is a fundamental information in these networks, affect the inferences? To do this, we apply supervised and unsupervised learning techniques to predict network type -- Mobile or WiFi, application name, and user ID. Our results present an overview of how knowledge can be extracted from data shared by users, and which type of data is the most revealing.
Diurnal changes of blood pressure values (24 h blood pressures) in women with polycystic ovary syndrome Rytm dobowy ciœnienia têtniczego u kobiet z zespo³em policystycznych jajników

Summary Background: More attention is being paid lately to polycystic ovary syndrome (PCOS) not only in the aspect of fertility but also according to long-term metabolic and cardiovascular abnormalities. Observations of women with PCOS show that the occurrence of blood hypertension is more frequent after the menopause. There are few articles concerning the predictable symptoms of blood hypertension. It seems that twenty-four hour blood pressure monitoring and assessment of changes of diurnal rhythm could be useful in this group of patients. Aim of the study: The purpose of this study was to assess diurnal changes of blood pressure in women with polycystic ovary syndrome. Material and methods: 26 women with PCOS diagnosed according to Rotterdam consensus criteria and Androgen Excess Society (AES) criteria were included in our study. The mean age of the examined women was 29.5 years and the mean BMI (body mass index) was 24.7 kg/m 2 . The control group consisted of 12 age-matched women, without PCOS. Twenty-four hour Holter monitoring of ambulatory blood pressure was performed during normal daily activity in all patients. Halberg’s cosinor method was used to analyse daily biorhythm. Results: Results show the diurnal changes of systolic blood pressure in the preclinical phase in 30% and diastolic in 15% of PCOS women. In this group no physiological decrease of blood pressure at night time was observed.
Serum adiponectin is related to resistin independent of adiposity

Adipocytokines secreted by adiposity and other tissues in known to have inflammatory and anti-inflammatory property. Adiponectin and resistin are two important adipokines and they have important role in obesity and chronic related diseases. This study was designed to determine the relationship between serum adiponectin as an antiinflammatory cytokine with resistin as a pro-inflammatory cytokine in thirty six sedentary adult men aged 38-44 years and body mass index, 32.56 ± 4.54 Kg/m2. For this purpose, participants fasted overnight to provide blood specimens and venous blood samples were collected of subjects. Blood samples were analyzed for measuring serum adiponectin and resistin. All anthropometrical variables were also measured. Serum adiponectin was not related with each anthropometrical marker (p≥0.05). In contrast, we observed that serum resistin was positively related anthropometrical indexes (p˂0.05). Serum adiponectin concentrations were negatively correlated with resistin, independent of BMI or fat tissue (P=0.000, r=0.77). Based on these data, we conclude the relationship between adiponectin and resistin levels were independent of adiposity in obese men.
New hexapod robot's arc legs design and optimization

Following the development of study in bionic mechanisms, several kinds of arc-legged robot structures have been derived. Despite having achieved excellent terrain adaptability, each of them had a fluctuated center of mass during the movement, which makes the load function out of order and reduces the stability in operations. To solve this problem, this paper proposes a new design of multi-segment arc-leg where the segments are cotangent to each other at the contact points. We designed a new arc-leg structure, and verified the advantages of the new arc-leg structure with small center of mass fluctuation in motion through calculation and simulation. In this paper, firstly, the model selection was carried out to establish the leg model of robot with different segments of arcs. ADAMS software was used for motion simulation experiment to observe the motion performance of different models. In the last stage of design, the optimal three-segment arc shaped structure was selected as the prototype for physical structure design. Secondly, parametric modeling and optimization were carried out. By setting constraints and establishing objective functions, we adopted simulated annealing algorithm to obtain optimal arc-leg structural parameters through multiple iterations. And then, a new type of arc-leg structure was adopted to carry out the robot motion simulation experiment, vibration simulation experiment. Through experimental comparison, it verified that the new type of arc-leg robot has achieved highly stable movement with low vibration, which can greatly reduce the working difficulty of the load modules. The design of the new arc-leg structure can make the future bionic robot have stronger terrain adaptability and promote its application in military operations, post-disaster rescue, dynamic monitoring and many other undiscovered fields.
C++ hard-real-time active library: syntax, semantics, and compilation of Tice programs

General-purpose programming languages C and C++ address only the functional aspect of programs. In contrast, real-time programming languages address not only the functional aspect but also the nonfunctional real-time aspect to automatically ensure the consistency of both aspects in the resulting code. Despite many real-time programming languages proposed in the literature, embedded and real-time programs for economical reasons have continued to be written in C/C++ with their real-time aspect being dealt separately using modeling tools (e.g., MATLAB/Simulink) and the consistency of both aspects being checked manually. As embedded and real-time systems permeate through people's lives, it becomes increasingly imperative that both aspects be kept consistent automatically to improve the reliability of the systems. To that end, we propose a real-time programming language called Tice with three novel features: (1) Tice programs are written as modern standard C++ programs. (2) Tice programs can be compiled using any modern off-the-shelf standard C++ compiler. (3) Tice programs compose with other C/C++ programs as C++ libraries. These novel features make Tice significantly more economical than other real-time programming languages proposed in the literature.
DCTP-A and DCTP-I: Collection Tree Protocols for Dual Radio Platforms

The use of two radios per node increases the energy efficiency of wireless sensor networks. Given that data collection is one of the most important functions in wireless sensor networks, this paper presents and compares two new data collection protocols for wireless sensor networks with two radios, DCTP-A and DCTP-I. DCTP-A builds the collection tree alternating the radio band each node while DCTP-I builds two independent collection trees. The protocols were implemented in TinyOS and evaluated experimentally in a testbed in the physical world using the 900MHz and 2.4GHz radio bands, compared to the state of the art (CTP and CTP-Multi) and to each other, considering the metrics delivery rate, latency, throughput in a saturated network scenario, total number of messages and the cost of maintaining routes. The results show the gain of the protocols for wireless sensor networks with two radios. DCTP-A achieved almost 100% of delivery rate, while DCTP-I achieved up to 90% delivery rate with less number of beacons messages.
EIGER: automated IOC generation for accurate and interpretable endpoint malware detection

A malware signature including behavioral artifacts, namely Indicator of Compromise (IOC) plays an important role in security operations, such as endpoint detection and incident response. While building IOC enables us to detect malware efficiently and perform the incident analysis in a timely manner, it has not been fully-automated yet. To address this issue, there are two lines of promising approaches: regular expression-based signature generation and machine learning. However, each approach has a limitation in accuracy or interpretability, respectively. In this paper, we propose EIGER, a method to generate interpretable, and yet accurate IOCs from given malware traces. The key idea of EIGER is enumerate-then-optimize. That is, we enumerate representations of potential artifacts as candidates of IOCs. Then, we optimize the combination of these candidates to maximize the two essential properties, i.e., accuracy and interpretability, towards the generation of reliable IOCs. Through the experiment using 162K of malware samples collected over the five months, we evaluated the accuracy of EIGER-generated IOCs. We achieved a high True Positive Rate (TPR) of 91.98% and a very low False Positive Rate (FPR) of 0.97%. Interestingly, EIGER achieved FPR of less than 1% even when we use completely different dataset. Furthermore, we evaluated the interpretability of the IOCs generated by EIGER through a user study, in which we recruited 15 of professional security analysts working at a security operation center. The results allow us to conclude that our IOCs are as interpretable as manually-generated ones. These results demonstrate that EIGER is practical and deployable to the real-world security operations.
Severe Hypercalcemia as the Initial Presentation of a Neuroendocrine Carcinoma of Unknown Primary Site: A Case Report

Hypercalcemia is a common paraneoplastic syndrome that is associated with many malignancies. Hypercalcemia develops in malignancies through various mechanisms. Parathyroid hormone-related protein (PTHrP) is secreted by malignancy involving the lungs, breast, colorectum, bladder, and, rarely, neuroendocrine tumors. This is a rare case of severe hypercalcemia as the initial presentation of a high-grade metastatic neuroendocrine tumor of an unknown primary site.
QUALITATIVE STUDY TO FIND THE BEHAVIOR OF INDIVIDUAL INVESTORS IN EAST JAVA , INDONESIA

This study responds to the separation of the rational behavioral perspective and the irrational behavior perspective on the Behavioral Finance through the identification and investigation of how investors behave when making investment decisions. Researcher is interested in doingan explorative identification and investigation on the behavior of investors when making investment decisions. The perspective of neuroeconomics is used as tool to analyze the phenomena. This research uses qualitative postpositivism paradigm with Grounded Theory method. The proposition successfully constructed in this study are for as follows: Cognitive or affective behavior of individual investors in making investment decisions generated by the response of dynamic brain regions. The regions are orbitofrontal cortex (OFC), the ventromedial prefrontal cortex (vmPFC), the dorsolateral prefrontal cortex (DLPFC), anterior cingulate cortex (ACC) and the amygdala in assessing the consequences of events market and its resources.
Python Enabled ParaViewWeb for HPC Analysis and Visualization

ParaViewWeb uses ParaView, an open-source, parallel, data analysis and visualization framework, to generate data products on the server-side and rapidly deliver those data products over the Internet to a web client. Since version 4.0 of ParaView, using ParaViewWeb technologies provides access to all of ParaView through Python interfaces using pvpython or pvbatch. Using a Python script and leveraging the Python interpreter, ParaViewWeb exposes ParaView’s HPC large data analysis and visualization capabilities through a web server. ParaViewWeb allows the user to perform computationally intensive analysis and visualization tasks within a Web browser by relying on a remote, and possibly distributed, ParaView server for parallel processing and/or rendering. In this paper, we present the new python-enabled ParaViewWeb framework and demonstrate several use cases including its integration with iPython.
MEASURING THE DEGREE OF MARKET POWER AMONG BROAD BEAN EXPORTERS TO EGYPT

Market power of exporting countries into a specific market is an important issue for decision makers within that market. It i s also an important issue for exporting countries since it can be related to the ability of the country to increase its access to the market. Competitiveness indicators including; comparative advantage, market share, market penetration rate, instability coefficient of exports, competitiveness of export price, compet itiveness of production, relative price, and relative stability of production in addition to residual demand model are used to measure the perfect competition conditions in the market and, accordingly, measure the market power of the different competitors. Australia, France, and UK are the more competitive exporting countries of Broad Bean to Egypt. However, China is a promising exporter with low prices and stable production. KeywordsMarket power, Competitiveness, Residual demand, Egypt, Bean
Charged black holes in string-inspired gravity

We investigate gravitational collapses of charged black holes in string-inspired gravity models, including dilaton gravity and braneworld model, as well as f(R) gravity and the ghost limit. If we turn on gauge coupling, the causal structures and the responses of the BransDicke field depend on the coupling between the charged matter and the Brans-Dicke field. For Type IIA inspired models, a Cauchy horizon exists, while there is no Cauchy horizon for Type I or Heterotic inspired models. For Type IIA inspired models, the no-hair theorem is satisfied asymptotically, while it is biased to the weak coupling limit for Type I or Heterotic inspired models. Apart from string theory, we find that in the ghost limit, a gravitational collapse can induce inflation by itself and create one-way traversable wormholes without the need of other special initial conditions.
Understanding the brain keeps the score. IV. Interface between impairment and ethical violations. V. Mitigating compassion fatigue; what is the formula for staying fit to practice

Although secondary trauma has been assessed in various groups of mental health professionals, few studies, to date, have examined secondary trauma among attorneys exposed to clients’ traumatic experiences. This study examined indicators of secondary trauma among attorneys (N = 238) and their administrative support staff (N = 109) in the Wisconsin State Public Defender Office. Attorney participants demonstrated significantly higher levels of posttraumatic stress disorder symptoms, depression, secondary traumatic stress, burnout, and functional impairment compared with the administrative support staff. This difference was mediated by attorneys’ longer work hours and greater contact with clients who had experienced or had been directly involved with trauma. Sex, age, years on the job, office size, and personal history of trauma did not predict symptoms. These findings suggest a need to support attorneys experiencing these symptoms and to address high workloads as well as the intensity of contact with trauma-exposed clients.
Physiological response of Ostreococcus to nutrient depletion

Phytoplankton are an important primary producer, which populate all of the oceans on Earth. One of the key environmental variables that control population growth of phytoplankton is nutrient availability. With rising levels of carbon dioxide in our atmosphere and increasing density stratification due to warming oceans, the nutrients available to phytoplankton in the euphotic zone will change. To further understand the nutrient limitation of phytoplankton, I investigated how the growth rate and elemental quotas of the pico-phytoplankton Ostreococcus respond to the depletion of nitrogen and phosphorus. I addressed this question by monitoring the growth of Ostreococcus cultures in multiple nutrient conditions (nutrient replete and deplete) using flow cytometry. In addition to calculating growth rates, I collected samples for cellular elemental quotas from the different treatments and across different phases of growth. These results will provide insight into the physiological plasticity of phytoplankton, which is a poorly characterized parameter in current biogeochemical models. Ultimately, the results of this study will give us a deeper understanding of the role of phytoplankton in marine biogeochemical cycles and how their populations may be affected in the future.
MPERL: Hardware and Software Co-design for Robotic Manipulators ©

Building small custom robots is getting democratized thanks to affordable tools like 3D printers and micro controllers. However, it still requires expertise from a wide range of domains: from designing the mechanical parts to writing the code that controls the robot. We present MPERL, a tool to help non-experts build custom robotic manipulators. MPERL starts from an abstract description of the robot’s kinematic structure which contains information about joints, actuators, and sensors. The structure is refined with an easily manufactured geometry. Furthermore, from the structure MPERL generates control code which can be used to move the robot to a target configuration. We evaluate MPERL on a range of common robotic manipulator architectures, both serial and parallel.
Traveling wave solutions in a higher dimensional lattice competition-cooperation system with stage structure

In this paper, we consider the existence of traveling wave solutions in a higher dimensional lattice competition-cooperation system with stage structure. We first construct a pair of upper and lower solutions. The upper solutions are allowed to be larger than positive equilibrium point. Then we establish the existence of traveling wave solutions by means of cross iterative and Schauder's fixed point theorem.
AN OVERVIEW OF EXISTING EVALUATION METRICS FOR 3D MESH SEGMENTATION

The evaluation of mesh segmentation has received a great deal of attention since 3D mesh segmentation is an essential step in many mesh operations. For this reason, notable efforts have been made towards a better evaluation of mesh segmentation methods, and one of the most popular works is the benchmark of Chen et al., which allows a quantitative evaluation of mesh segmentation algorithms. Based on the given data sets, which comprise manual and automatic segmentations, many evaluation metrics have been proposed recently. In this context, we present in this study an overview of the existing similarity metrics and new ones proposed in our previous works addressing the problem of evaluating 3D mesh segmentation by describing each method and giving an extensive study and experimental comparison of them.
A Theoretical Framework for Describing Effects of Virtual Interactivity between Government and Citizens: The Chicago Police Department’s Citizen ICAM Application

This paper considers the current efforts to describe the effect of Internet-based technology on interactivity between citizens and public organizations to be incomplete and poorly linked. This paper develops a model of interactivity that reflects the self-organization potential of virtual communication and the social context within which citizens and bureaucrats operate. The model helps us to identify ways in which different levels of feedback communication, e.g., email, may affect change in organizations, communities, and the relationship between organizations and communities. A case analysis of the Chicago Police Department’s (CPD) Citizen ICAM is reviewed to determine the effects of feedback and the technology on the organization. We find that virtual interactivity is a complex process – more complex than typically described – that has significant effects on the structure and work processes of the CPD. We conclude by proposing a staged model of citizen-government interactivity and by identifying future research directions.
PREPARATION OF NANOCRYSTALLINE CELLULOSE FROM TOMATO STEM AND COMMERCIAL MICROCRYSTALLINE CELLULOSE: A COMPARISON BETWEEN TWO STARTING MATERIALS

Nanocrystalline cellulose was prepared from locally abundant tomato stem. Initially, chemical treatment was performed to remove the non-cellulosic constituents of tomato stem. Isolation involves a combination of acid hydrolysis and ultrasonic treatment. The shape and size distribution of the resulting NCC were determined using particle size analysis, scanning electron microscopy (SEM) and transmission electron microscopy (TEM) images. The thermal properties, surface functional groups, sulfur content and crystallinity of the NCC derived from tomato stem were compared to those of the NCC prepared from commercial microcrystalline cellulose (MCC). The morphology of NCC obtained from tomato stem has an interconnected web-like structure and the crystallinity index was calculated as 74.4%. The suspension of the NCC derived from tomato stem was very stable and could be stored for at least three months without sedimentation, which was confirmed by particle size and zeta potential measurements. The economic competitiveness of NCC production is dependent on feedstock costs. As demonstrated in this study, waste tomato stem can be a good low-cost alternative for NCC isolation.