Miracle-dz/UniFAR-FTUs huggingface dataset:
Variety and management of developmental conflicts: the case of the Olkaria IV geothermal energy project in Kenya

ABSTRACT The development of geothermal energy installations generates varied conflicts in Kenya that often escalate because of improper management. Yet, these developmental project conflict dynamics remain poorly understood. To better understand the dynamics of these conflicts, quantitative and qualitative data were collected from the Olkaria IV project-affected persons (PAPs) household heads using questionnaires, focus group discussions and key informant interviews. The qualitative data was arranged into socioeconomic, cultural, environmental and political themes and the proportion of respondents within each theme was calculated. The triggers for the conflicts included inadequate communication and participation in decision-making, unsatisfactory relocation logistics, and unfulfilled compensation promises. Also, the formulation and implementation of the resettlement action plan was inadequately negotiated with the PAPs. The effects of the conflicts on the PAPs’ livelihoods were severe. The conflicts were managed mainly through competition and avoidance strategies. Subsequent dissatisfaction on the part of the PAPs led to unrest that almost derailed the project. Planners need to be inclusive of the local community in the design of large development projects. Inclusiveness in planning would secure community buy-in, remove unrealistic pledges or expectations, and smoothen project implementation.
Optimal Scheduling of Urban Transit Systems Using Genetic Algorithms

Scheduling of urban transit network can be formulated as an optimization problem of minimizing the overall transfer time (TT) of transferring passengers and initial waiting time (IWT) of the passengers waiting to board a bus/train at their point of origin. In this paper, a mathematical programming (MP) formulation of the scheduling problem at one transfer station is presented. The MP problem is large and nonlinear in terms of the decision variables, thereby making it difficult for classical programming techniques to solve the problem. We apply genetic algorithms (GAs)-search and optimization methods based on natural genetics and selection-to solve the scheduling problem. The main advantage of using GAs is that the problem can be reformulated in a manner that is computationally more efficient than the original problem. Further, the coding aspect of GAs inherently takes care of most of the constraints associated with the scheduling problem. Results from a number of test problems demonstrate that the GAs are able to find optimal schedules with a reasonable computational resource. The paper concludes by presenting a number of extensions to the present problem and discusses plausible solution techniques using GAs. The success of GAs in this paper suggests their efficacy as a solution tool for similar optimization problems arising in transportation systems.
Keeping the Helicopters Flying—Using a Knowledge-Based Task Support System to Manage Maintenance

We used knowledge-based and object-oriented techniques to create the intelligent maintenance management system (IMMS). We developed IMMS to support maintenance officers in scheduling helicopters for maintenance at an air national guard base. Before the implementation of IMMS, maintenance officers were using a manual system to manage the scheduling process. However, they were encountering many scheduling problems. Solving these problems at the base pointed to a computer-based system. However, researchers have observed that computer-based systems have limitations in supporting decision makers in complex tasks. IMMS is a first attempt to overcome some of these limitations in a practical system. The system provides data, information, and decision-making assistance to the maintenance staff. IMMS is used on a daily basis and has proven to solve many of the management problems that the staff was having.
Possibility studies of integrated INS/RFID positioning methods for personal positioning applications

Precise positioning has been a challenging task in the areas of surveying, mapping, robotic movement control and especially personal navigation. To date, geodetic grade GPS systems such as Trimble R8, can provide a centimetre level of accuracy in real time over a large area using real-time kinematic (RTK) technique. However, the major drawbacks of the high accuracy GPS systems are expensive, not really portable and not suitable for indoor and urban canyon. Some alternative techniques, such as the micro-machined electromechanical system (MEMS) Inertial Navigation System (INS) and the radio frequency identification (RFID) positioning technique have recently become attractive. This is because these systems meet the needs of personal guidance and tracking applications due to their indoor positioning capability, simple infrastructure requirement, portability and low cost.
Development of a Modular In-Situ Oil Analysis Prognostic System

An in-situ system for analysis of lubricants and hydraulic oils is discussed. The system comprises specially designed X-ray fluorescence, non-dispersive infrared, and visco- metric modules, as well ferromagnetic and non-ferromagnetic particle detection. It is controlled by one or more microprocessors and can be incorporated directly into the lubrication systems of larger engines to provide near-real time information on oil chemistry, contamination, and wear materials. Oil analysis results can be automatically uploaded to remote locations by means of cell phone or other wireless technology.
Impact of unrealistic worst case modeling on the performance of VLSI circuits in deep sub-micron CMOS technologies

The impact of process fluctuations on the variability of deep sub-micron (DSM) VLSI circuit performances is investigated in this paper. In particular, we show that, as process dimensions scale down in the sub half-micron region, the relative weight of process variability tends to increase, thus wearing down a nonnegligible portion of the benefits that are expected from minimum feature size scaling. Therefore, in order to better exploit the advance of process technology, it is essential to adopt a realistic approach to worst case modeling, as in the assigned probability technique (APT) (Dal Fabbro et al, Proc. 32nd ACM/IEEE Design Automation Conf., pp. 702-6, 1995). The application of the APT technique to a 16-bit ripple-carry adder designed in 0.35 /spl mu/m, 0.25 /spl mu/m and 0.18 /spl mu/m CMOS technologies with a power supply ranging from 3.3 V down to 1 V demonstrates how the manufacturability of DSM designs is going to be a vital factor for the successful implementation of high performance or low-power systems in 0.18 /spl mu/m and lesser technologies.
Use of Intuition in Decision Making Among Managers in Banking and Industrial Sectors of Karachi

The study aims to explore the decision making processes of managers, working in banking and industrial sector in Karachi. Grounded theory research design is chosen to discover the ways in which managers choose to rely on intuition in decision making process. The proposed method consists of structured interview. The participants were theoretically selected, consists of 306 managers, aged 25 to 60 years (M = 47.89, SD = 17.58), 152 managers from banks and 154 from utility sector. All the responses were coded, then percentages of each response were calculated. Information generated through responses suggests that the use of intuition among managers is caused by uncertain situation and they develop work groups to make effective decisions in face of critical situation. It is hoped that outcomes of this study will allow us to develop better decision making strategies for the training of future managers.
Simulation Modeling of Urban E-Scooter Mobility

Shared micromobility is a rapidly growing transportation technology, with several companies establishing e-bike and e-scooter programs in cities all across the globe. In this paper, we use two years of empirical data on e-scooter usage from a pilot project in the City of Calgary to create a synthetic workload model of e-scooter traffic. Using this model, we develop a simulation environment to evaluate the impacts of different e-scooter management policies (e.g., fleet size, battery re-charging strategies, and urban parking infrastructure locations) on the efficacy of the e-scooter system. Our simulation results highlight the importance of proper site selection for parking areas and battery charging infrastructure.
Human Biopsies in Nanofibrillar Cellulose Hydrogel – A Novel Method for Long-term Tissue Culture

Advanced 3D in vitro models are laborious to prepare and susceptible to unintentional design errors due to culture adaptations, cell immaturity, xenofactors or yet incomplete knowledge of the dynamics within tissues or materials. In order to acquire cost-efficient research material with intact in vivo composition, we developed novel tissue culture method with plant-derived scaffolding. Human skin-, foreskin- and glioblastoma multiforme biopsies were dissected mechanically and cultivated for 28 days in plant-derived nanofibrillar cellulose hydrogel. Comparative cultures were done using mouse sarcoma tumor –derived Matrigel™. Long-term preservation of cultivated tissues was evaluated against typical immunohistochemical biomarkers for each tissue type: skin tissues for cytokeratins 5/6, E-cadherin and vimentin for sustained tissue structures, and brain neoplasia for Olig2, S100, Nestin, NOTCH1, MAP2 and GFAP for preserved disease profile. Histological analysis from both culture conditions showed that until day 28, all cultivated biopsy types were able to sustain their characteristic protein expressions without signs of necrosis. We here conclude a novel tissue culture model in xeno-free 3D scaffolding, that can enable long-term sample storage in vitro, studies of human tumor tissues and their non-neoplastic microenvironment, and innovations in personalized medicine research.
Design of electric dynamic load simulator based on recurrent neural networks

This paper describes the electric dynamic load simulator (DLS) driving by permanent magnet synchronous motor. It can reproduce desired load torque acting on loaded objective to test its performance. A simplified dynamic model is derived to clarify the causation of redundancy torque caused by the motion of loaded objective and illustrate the drawbacks of applying conventional control strategy. Real-time recurrent neural networks based iterative learning control strategy is adopted. It can restrain redundancy torque and improve the accuracy of load torque in spite of the nonlinearity and uncertainty in the system. The expected results have been obtained from simulation and experiment.
Design of a garment-based sensing system for breathing monitoring

The long-term monitoring of biophysiological signals requires new types of sensor systems that are wearable and at the same time convenient for the users. This paper describes the design of a novel garment-based sensing system for the long-term monitoring of breathing rhythm. The system concept was realized in a prototype garment, integrated with coated piezoresistive sensors. The prototype garment was tested by five subjects, and compared with a standard piezoelectric respiratory belt. Each signal was quantitatively and qualitatively evaluated in the time and frequency domain to make sure that no medical and diagnostic information was lost. The results showed a good agreement between the garment-based sensors and the standard reference, where errors occurred only when the breathing rate was extremely high. The garment-based sensor system could also distinguish the predominance breathing compartment (chest versus abdominal breathing). The system could detect a 10 s pause in breathing, which could be of importance in studies of sleep apnea. A garment-based sensing system maintains the accuracy of the signal quality without reducing the comfort for the user. It makes possible long-term ambulatory monitoring and has home-based healthcare applications.
On SPICE macromodelling of TiO 2 memristors

A SPICE macromodel is described which simulates the electrical behaviour of the recently discovered thin-film titanium dioxide (TiO 2 ) memristors. The macromodel allows for fast simulation of circuits that include memristors. The accuracy of the macromodel is demonstrated by comparison with the theoretical behaviour.
Green Diesel from Hydrotreated Vegetable Oil Process Design Study

A systematic approach was applied to study the process of hydrotreating vegetable oils. During the three phases of conceptual, detailed, and final design, unit operations were designed and sized. Modeling of the process was performed with UniSim Design®. Producing green diesel and jet fuel from vegetable oils was found to be technically possible via a flexible process of hydrotreatment. The resulting mass and energy balances indicated high carbon atom and energy yield. An economic evaluation proved that the operational expenses mainly depend on the cost of raw materials. Currently, the margin between crude palm oil and the retail diesel price is too low to operate an economically viable process. However, production and utilization of biofuels is required by international regulations.
Effects of Compost-Bedded Pack Barn on Circulating Cortisol and Beta-Endorphins in Dairy Cows: A Case Study

Simple Summary Management and housing conditions have been reported to significantly affect the health and welfare of livestock species. Therefore, the adoption of novel, alternative housing systems (such as the compost-bedded pack barn, developed in the USA) requires extensive research to assess the implications for animal welfare. From a general point of view, animal welfare is typically assessed by means of animal-based (such as blood biochemical markers) and resource-based (such as management practices) indicators. Based on such considerations, the present study evaluated the fluctuation of circulating cortisol and beta-endorphins in dairy cows housed in a conventional freestall barn (FB) and in the alternative compost-bedded pack barn (CB). The results obtained suggest that the CB housing system did not elicit significant changes in either blood cortisol or beta-endorphins. Abstract The up-to-date literature suggests that the compost-bedded pack barn housing system is capable of remarkably improving productive and reproductive performance, as well as health status and welfare, in dairy cattle. However, there is currently limited knowledge available on the endocrine and biochemical changes in animals housed in such alternative systems. Therefore, this study aimed to measure blood cortisol (COR) and beta-endorphins (BE) in 22 two-year-old primiparae Fleckvieh cows, who were randomly allotted to the following two different housing systems: CB (n = 11) and FB (n = 11). Blood samples were collected at the beginning of the experiment (T0) and every two months thereafter (T1, T2, and T3). The COR and BE were measured through an immunoenzymatic kit. With the only exception being T0, no differences were observed over time between the two groups, neither for COR nor for BE. However, the blood cortisol levels of the CB cows decreased over time, while a T1 peak was identified in the FB group. On the contrary, both the housing systems displayed numerically higher BE at T3 than at the other experimental times. Therefore, the overall data suggest that the compost-bedded pack barn did not significantly affect the studied parameters. Accordingly, cow welfare should be assessed using a wider panel of animal-based indicators.
Aide au paramétrage d'implant cochléaire par algorithme évolutionnaire

l'utilisation d'algorithmes evolutionnaires et sur l'expertise LE REGLAGE D'UN IC medicale ayant pour but de regler automatiquement les parametres determinants des implants cochleaires (IC). Ce L'objectif des reglages est d'optimiser l'information travail de recherche est realise en collaboration avec le delivree par l'implant par rapport aux capacites fabricant d'implants cochleaires MXM. Un Personal Data electrophysiologiques des voies auditives du patient [4]. Il Assistant (PDA) est mis a disposition du patient pour qu'il s'agit de privilegier les elements pertinents contenus dans puisse proceder de facon autonome au reglage de son la parole, de maniere a permettre une meilleure implant, dans l'environnement sonore qu’il souhaite et qu'il est souvent difficile de recreer dans la salle de consultation reconnaissance de celle-ci. Une cinquantaine de
Introduction to the Special Issue on Man aging Information Extraction

The field of information extraction (IE) focuses on extracting structured data, such as person names and organizations, from unstructured text. This field has had a long history. It attracted steady attention in the 80s and 90s, largely in the AI community. In the past decade, however, spurred on by the explosion of unstructured data on the World-Wide Web, this attention has turned into a torrent, gathering the efforts of researchers in the AI, DB, WWW, KDD, Semantic Web and IR communities. New IE problems have been identified, new IE techniques developed, many workshops organized, tutorials presented, companies founded, academic and industrial products deployed, and opensource prototypes developed (e.g., [5, 4, 3, 1, 2]; see [5] for the latest survey). The next few years are poised to witness even more accelerated activities in these areas. It is against this vibrant backdrop that we assemble this special issue. Our objective is threefold. First, we want to provide a glimpse into the current state of the field, highlighting in particular the wide range of IE problems. Second, we want to show that many IE problems can significantly benefit from the wealth of work on managing structured data in the database community. We believe therefore that our community can make a substantial contribution to the IE field. Finally, we hope that examining IE problems can in turn help us gain valuable insights into managing data in this Internet-centric world, a long-term goal of our community. Keeping in mind the above goals, we end this introduction by briefly describing the nine papers assembled for the issue. These papers fall into four broad categories.
Testing roadmap for generalized agile framework

Testing in Agile development frameworks has engaged the concentration of software developers throughout the world. The research regarding this testing is however limited. This paper comprises a literature survey study, which intends to categorize and examine the current existing testing frameworks in agile methodology. The comparative study is done with the Test Driven Development (TDD) and Agile Model Driven Development (AMDD) techniques. The results show the benefits and drawbacks of the current existing testing frameworks in agile methodology in general. However many techniques still make every effort to get the general solutions. Basing on our results general ideas are suggested regarding the testing frameworks in agile methodology.
Hypoalbuminemia Is Associated with Increased 30-Day Complications following Rectourethral Fistula Repair: A National Surgical Quality Improvement Program Study

Abstract Introduction: We sought to assess patient risk factors for 30-day postoperative complications among men undergoing surgical management of rectourethral fistula (RUF). Methods: The American College of Surgeons National Surgical Quality Improvement Program database was queried for all male patients who underwent RUF repair (2006–2018). Hypoalbuminemia was defined as preoperative serum albumin <3.5 gm/dL. Postoperative 30-day complications included wound infection, organ space surgical site infection, urinary tract infection, sepsis, venous thromboembolism, pneumonia, cerebrovascular accident, myocardial infarction, return to operating room and mortality. The association between pre-selected patient covariates and postoperative complications was investigated using logistic regression analysis. Results: A total of 250 patients were identified. Concurrent procedures during RUF repair were bowel diversion in 43/250 patients (17.2%), bowel resection (34/250, 13.6%), cystectomy (20/250, 8.0%) and urethroplasty (37/250, 14.8%). Overall, median age was 66.0 years (IQR 59.0–72.0), body mass index 26.6 kg/m2 (IQR 23.7–29.5) and 247/250 patients (98.8%) were functionally independent. Comorbidities included hypertension (140/250, 56.0%), smoking (55/250, 22.0%), diabetes (17/250, 6.8%), chronic obstructive pulmonary disease (11/250, 4.4%) and congestive heart failure (1/250, 0.4%). Hypoalbuminemia (<3.5 gm/dL) was present in 25/126 patients (19.8%). Overall, 51/250 patients (20.4%) experienced a complication within 30 days of surgery including wound infection (14/250, 5.6%), sepsis (13/250, 5.2%), organ space infection (11/250, 4.4%), urinary tract infection (8/250, 3.2%), venous thromboembolism (8/250, 3.2%) and mortality (5/250, 2.0%). After adjusting for covariates, hypoalbuminemia was associated with increased odds of a 30-day complication (OR 2.49, 95% CI 1.06–5.86, p=0.036). Conclusions: Hypoalbuminemia was associated with increased odds of short-term complications after surgical management of RUF.
Planning safe motion for 2- and 3-DOF manipulators by computing an approximate medial axis of the free configuration space

We propose a novel two-phase approach for planning the safe motion of a robot. First, in a preprocessing phase, an approximation of the medial axis of the free configuration space is constructed through: 1) a probing of the full configuration space along a grid, and 2) a careful selection of a subset of grid configurations that are likely to lie near the actual medial axis. Though the selection process is akin to skeletonization in digital image processing our implementation differs owing to the particular requirements of motion planning. In a subsequent planning phase, a given start-goal configuration pair is first connected to the medial axis by an inexpensive local planner, and then a motion is planned as a path within the medial axis. Experiments with 2- and 3-DOF manipulators show that the approach generates longer but significantly safer motion compared to a naive planning approach that always finds a shortest motion. In addition, once preprocessing is completed our approach spends much less time for planning than the naive approach. Variations of this approach hold possibilities for extension to robots with many DOF.