High Level Of Certainty Research Articles

Pakistani Opposition to American Drone Strikes

AMERICA’S EMPLOYMENT OF WEAPONIZED unmanned aerial vehicles (UAVs), popularly known as “drones,” to kill alleged terrorists in Pakistan’s federally administered tribal areas (FATA) fuels sustained controversy in Pakistan. Pakistani outrage has steadily deepened since 2008, when the United States increased the frequency of the strikes.1 The increasing use of “signature strikes” has been particularly controversial in (and beyond) Pakistan, because such strikes are targeted at “men believed to be militants associated with terrorist groups, but whose identities aren’t always known.”2 Whereas personality strikes require the operator to develop a high level of certainty about the target’s identity and location, based on multiple sources such as “imagery, cell phone intercepts and informants on the ground,”3 operators may “initiate a signature strike after observing certain patterns of behavior.”4 When conducting signature strikes, the United States assesses that the individuals in question exhibit behaviors that match a pre-identified “signature” (for example, pattern of observable activities and/or personal networks) that suggests that they are associated with al Qaeda and/or the Pakistani or Afghan Taliban organizations.5 Because the identity of the target is unknown, even during the strike, it is possible that these persons are innocent civilians, a possibility that both current and former U.S. government officials concede.6 While the George W. Bush administration employed both personality strikes from 2004 and signature strikes from 2008 in Pakistan, the administration of Barack Obama has redoubled the use of both types.7 This has ignited public protests against the drones in Pakistan, particularly in Pakistan’s urban areas—far removed from the tribal areas where drones are employed. It has also galvanized a vigorous debate within Pakistan’s National Assembly, which tried, but ultimately failed, to curtail the strikes.

A machine-learning approach for structural damage detection using least square support vector machine based on a new combinational kernel function

Health assessment and monitoring of engineered systems have become one of the fastest growing multi-disciplinary research areas over the last two decades. One of the largest concerns in structural health monitoring is how to infer structural conditions from the measurements and the data collected by sensors. The ultimate aim is to detect the structural damages with a high level of certainty and hence to extend the life of structures. In this study, a new strategy for structural damage detection is proposed using least square support vector machines based on a new combinational kernel. Thin plate spline Littlewood–Paley wavelet kernel function introduced in this article is a novel combinational kernel function, which combines thin plate spline radial basis function kernel with local characteristics and a modified Littlewood–Paley wavelet kernel function with global characteristics. During the process of structural damage detection, a social harmony search algorithm optimizes the parameters of least square support vector machine and the thin plate spline Littlewood–Paley wavelet kernel. The results obtained by this method are compared with least square support vector machine based on the other combinational and conventional kernels. These results show that the accuracy of damage detection based on least square support vector machine with thin plate spline Littlewood–Paley wavelet kernel is higher than other methods that utilize conventional kernels under similar conditions. In comparison with other combinational kernels, least square support vector machine with thin plate spline Littlewood–Paley wavelet kernel possesses a better dissemination and learning ability by incorporating the advantages of radial basis function kernel and wavelet kernel functions.

Use of expert knowledge to elicit population trends for the koala (Phascolarctos cinereus)

AbstractAimThe koala is a widely distributed Australian marsupial with regional populations that are in rapid decline, are stable or have increased in size. This study examined whether it is possible to use expert elicitation to estimate abundance and trends of populations of this species. Diverse opinions exist about estimates of abundance and, consequently, the status of populations.LocationEastern and south‐eastern AustraliaMethodsUsing a structured, four‐step question format, a panel of 15 experts estimated population sizes of koalas and changes in those sizes for bioregions within four states. They provided their lowest plausible estimate, highest plausible estimate, best estimate and their degree of confidence that the true values were contained within these upper and lower estimates. We derived estimates of the mean population size of koalas and associated uncertainties for each bioregion and state.ResultsOn the basis of estimates of mean population sizes for each bioregion and state, we estimated that the total number of koalas for Australia is 329,000 (range 144,000–605,000) with an estimated average decline of 24% over the past three generations and the next three generations. Estimated percentage of loss in Queensland, New South Wales, Victoria and South Australia was 53%, 26%, 14% and 3%, respectively.Main conclusionsIt was not necessary to achieve high levels of certainty or consensus among experts before making informed estimates. A quantitative, scientific method for deriving estimates of koala populations and trends was possible, in the absence of empirical data on abundances.

The Influence of Emotion on Trust

Political scientists frequently wish to test hypotheses about the effects of specific emotions on political behavior. However, commonly used experimental manipulations tend to have collateral effects on emotions other than the targeted emotion, making it difficult to ascribe outcomes to any single emotion. In this letter, we propose to address this problem using causal mediation analysis. We illustrate this approach using an experiment examining the effect of emotion on dyadic trust, as measured by the trust game. Our findings suggest that negative emotions can decrease trust, but only if those negative emotions make people feel less certain about their current situation. Our results suggest that only anxiety, a low-certainty emotion, has a negative impact on trust, whereas anger and guilt, two emotions that differ in their control appraisals but induce the same high level of certainty, appear to have no effect on trusting behavior. Importantly, we find that failing to use causal mediation analysis would ascribe apositiveeffect of anxiety on trust, demonstrating the value of this approach.

Interobserver Agreement in the Classification of Pancreatic Cysts With Needle-Based Confocal Laser Endomicroscopy

Introduction: Needle-based confocal laser endomicroscopy (nCLE) may serve as an accurate and clinically relevant adjunct in classifying pancreatic cysts. The question remains whether clinician interpretation of nCLE images is consistent enough to render nCLE a precise tool. The aim of this study was to determine our institutional interobserver agreement for interpretation of nCLE images of pancreatic cysts. Methods: All pancreatic cyst EUS-FNA cases with nCLE from 3/2014-4/2015 at a large tertiary medical center were included. 3 interventional endoscopists who independently had performed the cases reviewed all nCLE images in a blinded manner and classified each case as serous cystadenoma (SCA), intraductal papillary mucinous neoplasm (IPMN), neuroendocrine tumor (NET), or other. Each clinician designated diagnostic certainty (certain/uncertain) and image quality (poor/fair/good). The primary outcome was interobserver agreement in pancreatic cyst classification, as calculated by the Fleiss kappa in SAS 9.3. Secondary outcomes were accuracy of individual and group diagnosis, as compared to overall cyst clinical impression as previously determined by the performing endoscopist, based upon radiology studies, EUS, nCLE, CEA/amylase, cytology and surgical pathology.Table 1: Interobserver Agreement in Pancreatic Cyst Evaluation with nCLEResults: 14 cases were included. Interobserver agreement was “fair to good” (kappa=0.65, p=0.003). nCLE diagnosis by the performing endoscopist was accurate in 11/14 cases. Blinded accuracy was 43%, 50%, and 57%, respectively. Majority consensus, with at least 2 of 3 clinicians independently achieving the same diagnosis, occurred in 12/14 cases. Consensus accuracy was 58% and increased to 67% in cases of unanimous agreement. There was little correlation between consensus diagnostic accuracy and certainty. In all instances of unanimous agreement, regardless of diagnostic accuracy, there was high level of certainty. Image quality appeared to have limited impact on achieving consensus or the accuracy of consensus diagnosis. Conclusion: Our prior work has shown that nCLE enhances accuracy in classifying pancreatic cysts and is clinically relevant in preventing referral for surgical resection. Interobserver agreement is high demonstrating the reliability of this tool, yet both individual and group diagnostic accuracy fell short of that of the performing endoscopist, indicating that clinical context is vital to nCLE's utility. Clinicians would benefit from greater training with nCLE to improve the yield of this new technology.

Defining safe criteria to diagnose miscarriage: prospective observational multicentre study

Objectives To validate recent guidance changes by establishing the performance of cut-off values for embryo crown-rump length and mean gestational sac diameter to diagnose miscarriage with high levels of certainty....

Risk factors for shoulder pain and injury in swimmers: A critical systematic review

Swimming is one of the most popular recreational and competitive sporting activities. In the 2013/2014 swimming season, 9630 men and 12,333 women were registered with the National Collegiate Athletics Association in the USA. The repetitive nature of the swimming stroke and demanding training programs of its athletes raises a number of concerns regarding incidence and severity of injuries that a swimmer might experience during a competitive season. A number of risk factors have previously been identified but the level of evidence from individual studies, as well as the level of certainty that these factors predispose a swimmer to pain and injury, to our knowledge has yet to be critically evaluated in a systematic review. Therefore, the primary objective of this review is to conduct a systematic review to critically assess the published evidence for risk factors that may predispose a swimmer to shoulder pain and injury. Three electronic databases, ScienceDirect, PubMed and SpringerLink, were searched using keywords “(Injury OR pain) AND (Swim*)” and “(Shoulder) AND (Swim*)”. Based on the inclusion and exclusion criteria, 2731 unique titles were identified and were analyzed to a final 29 articles. Only articles with a level of evidence of I, II and III were included according to robust study design and data analysis. The level of certainty for each risk factor was determined. No studies were determined to have a high level of certainty, clinical joint laxity and instability, internal/external rotation, previous history of pain and injury and competitive level were determined to have a moderate level of certainty. All other risk factors were evaluated as having a low level of certainty. Although several risk factors were identified from the reviewed studies, prospective cohort studies, larger sample sizes, consistent and robust measures of risk should be employed in future research.

Efecto de factores temáticos y pragmáticos en razonamiento condicional con textos narrativos

RESUMEN En esta investigación experimental se analiza la importancia de factores de tipo temático y pragmático en tareas de inferencia condicional, incluidas en textos narrativos, que describen situaciones plausibles de la vida cotidiana. Se manipula el tipo de contenido (causal versus promesa/amenaza), la congruencia de los textos (congruente versus no congruente), la probabilidad de ocurrencia empírica de los enunciados condicionales (deterministas, probabilísticos y ninguna relación), y el tipo de regla condicional (Modus Ponens, Modus Tollens, Afirmación del Consecuente y Negación del Antecedente). A partir de un paradigma de selección de respuesta, además de elegir la conclusión, los sujetos debían indicar la seguridad con la que hacían dicha selección. Los resultados pusieron de manifiesto que: (a) Los sujetos que razonaban con textos congruentes, obtenían mejores resultados y manifestaban sentirse más seguros de sus respuestas que los que razonaban con textos no congruentes; (b) se obtuvieron las tasas más elevadas de aciertos y la mayor seguridad en las respuesta cuando se razonaba con enunciados deterministas, que siempre suceden en el mundo real (c) el tipo de contenido no registró efectos principales, pero sí se obtuvieron efectos interactivos significativos entre el contenido y la congruencia de los textos. Los resultados obtenidos se discuten en el marco de los principales enfoques teóricos actuales de razonamiento condicional.

MITIGATING HYPOTHETICAL BIAS IN STATED PREFERENCE DATA: EVIDENCE FROM SPORTS TOURISM

One of the major criticisms of stated preference data is hypothetical bias. Using a unique dataset of both stated and actual behavior, we test for hypothetical bias of stated preference survey responses. We consider whether respondents tend to overstate their participatory sporting event behavior ex ante when compared to their actual behavior at different registration fees. We find that stated behavior accurately predicts actual behavior at a middle level of respondent certainty, overpredicts actual behavior at a lower level of certainty, and underpredicts behavior at a higher level of certainty. This result suggests that respondent uncertainty corrections can be used to mitigate hypothetical bias and stated preference data can be used to better understand actual behavior in situations where no data exist. (JEL L83, Q51, Z2)

Gender Differences of Physics Major College Students' Conceptual Understanding and Its Degree of Certainty in the Subject of Quantum Mechanics

This study aims to investigate the gender differences of college students concerning the levels of their understandings on the six major concepts in Quantum Mechanics (QM) and the degree of certainty of their knowledge. For this purpose, 182 physics major college students responded to the revised Quantum Mechanics Conceptual Survey (QMCS) and the Scale for Degree of Certainty on their Knowledge (SDCK). In the results, male students presented statistically-significant higher mean scores on both the QMCS and the SDCK. Specifically, female students held insufficient knowledge of ‘wave-particle duality’ and the ‘wave function’. In addition, a significant correlation between the scores on the QMCS and the SDCK was observed in both gender groups. The students presented decent levels of understanding on the concept of ‘quantization of states’ with a high level of certainty whereas they struggled to understand the concepts of ‘wave-particle duality’, ‘tunneling effect’ and ‘Schrodinger equation’ with a low degree of certainty.

A Supply Chain Financial Management Insurance Model for the Protection of Corporations Against the Bankruptcy of Suppliers by Using the Black-Scholes-Merton Model

Many banks provide supply-chain finance solutions that might include insurance services that further mitigate trade risk such as the default of suppliers. This study proposes the development of an insurance model that uses the Black-Scholes-Merton Model (BSM) (1973) for default prediction and risk pooling management techniques as a way to reduce the risk due to supplier bankruptcy and estimate an insur-ance premium that banks can use to charge this service to their customers. In order to demonstrate the use of the proposed insurance model, a sample of companies is selected from the New York Stock ex-change and data for historical stock prices from the CRSP database (Center for Research in Security Prices) is collected in order to calculate the probability of bankruptcy of a sample of suppliers from differ-ent industries by using the BSM model. Twelve pools of companies of different sizes are created and a VBA program for Excel is developed in order to calculate probability of bankruptcy tables of companies belonging to the different pools. A Monte Carlo simulation to simulate the impact on risk and expected losses on the number of insurance policies sold is implemented with the use of simulation software. The results show that the simulation is useful to estimate the number of sold policies required in order to reduce the risk to a minimum level and predict with a high level of certainty the losses due to bankruptcy of suppliers. The expected losses for a risk pool can be used by a financial institution in order to price an insurance contract that hedges a company against the risk of default of suppliers.

Mandatory versus voluntary payment for green electricity

Renewable energy sources have a critical role to play in contributing to the diversity, sustainability and security of energy supplies. The main objective of the paper is to gain an understanding of the support mechanism of renewable energy sources most preferred by households in the United Kingdom. This paper analyses households' preferences and willingness to pay under a mandatory scheme where all households contribute compared to a voluntary scheme where only those who wish to pay to support renewables do so (such as the green tariffs offered by electricity suppliers in the UK). Two contingent valuation method (CVM) surveys are used to explore whether the type of payment option has an impact on households' willingness to pay (WTP) for increasing share of renewable energy in electricity generation. The paper also investigates whether the type of payment mode affects respondents' self-reported certainty of paying their stated valuations. The results indicate that the likelihood of paying a positive amount for supporting renewable energy is higher under a mandatory scheme compared to a voluntary payment option in the UK. Respondents have a higher level of certainty in paying their stated WTP under a mandatory payment scheme.

Replicate Measurements of Haemoglobin Mass during a Single Day are Feasible and Precise.

Duplicate haemoglobin mass (Hbmass) measurements are recommended before and after altitude training sojourns to identify individual adaptations in athletes with a high level of certainty. Duplicate measurements reduce typical error (TE) and disclose measurement outliers, but are usually made on separate days, which is not a practical protocol for routine services in elite sport settings. The aim of this study was therefore to investigate whether it is safe (carboxyhaemoglobin<10%) to measure Hbmass twice on the same day and to compare TE with measurements made on separate days. 18 healthy men completed 3 different procedures to measure Hbmass twice a day with the carbon monoxide rebreathing method: A (Hbmass measured twice within 6 h), B (dito A, combined with 1 h of hyperoxic training between the tests), C (dito B, within 2 h). First Hbmass measurements of the 3 test days served as procedure D. Carboxyhaemoglobin did not exceed 10% in any procedure. TE and confidence limits for procedures A, B, C and D were 1.4% (1.0-2.1%), 1.1% (0.8-1.7%), 1.3% (1.0-2.0%) and 1.5% (1.2-2.1%), respectively. Duplicate measurements of Hbmass on the same day are feasible and show TE similar to triplicate measurements on separate days.

Generation of daily global solar irradiation with support vector machines for regression

Solar global irradiation is barely recorded in isolated rural areas around the world. Traditionally, solar resource estimation has been performed using parametric-empirical models based on the relationship of solar irradiation with other atmospheric and commonly measured variables, such as temperatures, rainfall, and sunshine duration, achieving a relatively high level of certainty. Considerable improvement in soft-computing techniques, which have been applied extensively in many research fields, has lead to improvements in solar global irradiation modeling, although most of these techniques lack spatial generalization.This new methodology proposes support vector machines for regression with optimized variable selection via genetic algorithms to generate non-locally dependent and accurate models. A case of study in Spain has demonstrated the value of this methodology. It achieved a striking reduction in the mean absolute error (MAE) – 41.4% and 19.9% – as compared to classic parametric models; Bristow & Campbell and Antonanzas-Torres et al., respectively.

Estimation of solar global irradiation in remote areas

Solar global irradiation is barely recorded in remote areas around the world. The lack of access to an electricity grid in these areas presents an enormous opportunity for electrification through renewable energy sources and, specifically, with photovoltaic energy where great solar resources are available. Traditionally, solar resource estimation was performed using parametric-empirical models based on the relationship between solar irradiation and other atmospheric and commonly measured variables, such as temperatures, rainfall, sunshine duration, etc., achieving a relatively high level of certainty. The significant improvement in soft-computing techniques, applied extensively in many research fields, has led to improvements in solar global irradiation modeling. This study conducts a comparative assessment of four different soft-computing techniques (artificial neural networks, support vector regression, M5P regression trees, and extreme learning machines). The results were also compared with two well-known parametric models [Liu and Scot, Agric. For. Meteorol. 106(1), 41–59 (2001) and Antonanzas-Torres et al., Renewable Energy 60, 604–614 (2013b)]. A striking mean absolute error of 1.74 MJ/m2 day was achieved with support vector regression (around 10% lower than with classic parametric models). Furthermore, the annual sums of estimated solar irradiation with this technique were within the intrinsic tolerance of pyranometers (5%). This methodology is performed in free environment R software and released at www.github.com/EDMANSOLAR/remote for future replications of the study in different areas.

A physical match of a metallic chip found on a bolt cutters' blade.

Bolt cutters are known as devices which are used for cutting hard objects and rigid materials such as padlocks and bars. They are commonly used in instances of forced entries. In this case study, a bolt cutter was found in the car of two suspects in a grocery burglary. This study indicates how the presence of a small metallic chip found on a suspected bolt cutter can prove that the tool was used in the crime scene. During the initial examination, a metallic chip from the cut shackle padlock was found stuck to one of the bolt cutters' blades. By comparing the metallic chip's microscopic edge and the breaking (fracture) line of the padlock's shackle, a full physical match was noticed. We wish to report here how residue, even the smallest, can be used to link burglary tools to a crime scene with a high level of certainty.

AN INSURANCE MODEL FOR THE PROTECTION OF CORPORATIONS AGAINST THE BANKRUPTCY OF SUPPLIERS BY USING THE BLACK-SCHOLES-MERTON MODEL

Many banks provide supply-chain finance solutions that might include insurance services that further mitigate trade risk such as the default of suppliers. This study proposes the development of an insurance model that uses the Black-Scholes-Merton Model (BSM) for default prediction and risk pooling management techniques as a way to reduce the risk due to supplier bankruptcy and estimate an insurance premium that banks can use to charge this service to their customers. In order to demonstrate the use of the proposed insurance model, a sample of companies is selected from the New York Stock exchange and data for historical stock prices from the CRSP database (Center for Research in Security Prices) is collected in order to calculate the probability of bankruptcy of a sample of sup- pliers from different industries by using the BSM model. Twelve pools of companies of different sizes are created and a VBA program for Excel is developed in order to calculate probability of bankruptcy tables of companies be- longing to the different pools. A Monte Carlo simulation to simulate the impact on risk and expected losses on the number of insurance policies sold is implemented with the use of simulation software. The results show that the simulation is useful to estimate the number of sold policies required in order to reduce the risk to a minimum level and predict with a high level of certainty the losses due to bankruptcy of suppliers. The expected losses for a risk pool can be used by a financial institution in order to price an insurance contract that hedges a company against the risk of default of suppliers.

Evidence-based Surgery for Cesarean Delivery

The objective of our systematic review was to provide updated evidence-based guidance for surgical decisions during cesarean delivery (CD). We performed an English-language MEDLINE, PubMed, and COCHRANE search with the terms, cesarean section, cesarean delivery, cesarean, pregnancy, and randomized trials, plus each technical aspect of CD. Randomized control trials (RCTs) involving any aspect of CD technique from Jan. 1, 2005, to Sept. 1, 2012, were evaluated to update a previous systematic review. We also summarized Cochrane reviews, systematic reviews, and metaanalyses if they included additional RCTs since this review. We identified 73 RCTs, 10 metaanalyses and/or systematic reviews, and 12 Cochrane reviews during this time frame. Recommendations with high levels of certainty as defined by the US Preventive Services Task Force favor pre-skin incision prophylactic antibiotics, cephalad-caudad blunt uterine extension, spontaneous placental removal, surgeon preference on uterine exteriorization, single-layer uterine closure when future fertility is undesired, and suture closure of the subcutaneous tissue when thickness is 2 cm or greater and do not favor manual cervical dilation, subcutaneous drains, or supplemental oxygen for the reduction of morbidity from infection. The technical aspect of CD with high-quality, evidence-based recommendations should be adopted. Although 73 RCTs over the past 8 years is encouraging, additional well-designed, adequately powered trials on the specific technical aspects of CD are warranted.

Dry Spells Occurrence in Tamale, Northern Ghana – Review of Available Information

Sustainable crop production is important for food security in Northern Ghana, where highly variable rainfall coupled with high evaporation rates and soils prone to degradation combine to produce low crop yields of main staple crops that are vital for local people’s livelihoods. Rainfall in this region generally ranges between 800 mm and 1200 mm per annum, falling within a single rainy season from April to October, with a peak in late August-September. This amount is adequate for most arable crops such as maize, rainfed rice, soybeans, and yams. Intermittent dry spells occur, however, at critical crop growth stages, resulting in significant yield reductions. Several studies conducted in this area show that dry spells can be expected during each annual rain season, with a high level of certainty and duration fromtwo to three days up to four weeks. This paper reviews both available literature on dry spell incidence and rainfall prediction in the West African region, with a particular focus on northern Ghana. Available daily rainfall data for 52 consecutive years are analyzed to determine dry spell duration and occurrence in northern Ghana.

Hemophagocytic Lymphohistiocytosis Associated With a Parvovirus B19 Infection During Pregnancy

Hemophagocytic lymphohistiocytosis is potentially fatal. Prompt diagnosis and initiation of treatment are critical for ensuring the best possible prognosis. We present a case of parvovirus B19 infection related to hemophagocytic lymphohistiocytosis during pregnancy. The patient experienced fever and pancytopenia. A bone marrow biopsy demonstrated hemophagocytosis and a giant proerythroblasts, which is characteristic of a parvovirus B19 infection. Viral serology for parvovirus B19 was positive. Prompt treatment was started because of the high level of certainty of viral-associated hemophagocytic lymphohistiocytosis, and the patient was successfully treated with prednisolone administration. She delivered a healthy newborn without any complications. Hemophagocytic lymphohistiocytosis should be considered when encountering unexplained cytopenia and fever. Prednisolone was an effective treatment.