Miracle-dz/UniFAR-FTUs huggingface dataset:
Stomatal-based inference models for reconstruction of atmospheric CO2 concentration: a method assessment using a calibration and validation approach

We investigated changes in atmospheric CO2 concentration (hereafter [CO2]) over the period AD 1700—2002 as reconstructed using the inverse relationship between stomatal frequencies (SF) of Betula nana leaves from northern Europe and [CO2]. The predictive ability of SF-inference models was assessed using a method of independent validation that involves two steps: (1) a training set of leaves grown between AD 1843 and 2002 was used to generate inference models; (2) the models were then applied to a fossil SF record of leaves grown between AD 1700 and 2002 that was split into two parts, a validation period (after AD 1850) and a reconstruction period (AD 1700—1850). Although our inference models had uncertainties comparable with other SF-inference models (root mean square error (RMSE) = c. 18—19 ppmv), uncertainties arising from the independent validation were larger (RMSE = c. 31—34 ppmv). Smoothed SF-inferred [CO 2] values after AD 1850 corresponded better to the industrial [CO 2] increase observed from instrumental records and from high-resolution ice cores, corroborating the accuracy of the reconstruction method in capturing a long-term (decadal- to centennial-scale) signal. This also indicates that in our record higher-frequency signals (eg, [CO2] maxima around AD 1750) are potentially less reliable. In an attempt to estimate the maximum reconstruction uncertainty (± 67 ppmv), we considered (i) the RMSE of the validation (validation error) and (ii) the maximum difference between reconstructions obtained with different inference models during the validation period (method error). We suggest that reconstruction uncertainties may be reduced by reducing the uncertainty of our inference models, with a subfossil record characterized by lower variability in the SF time series over the validation period, and by smoothing the reconstruction. This study shows that independent validation is an important step to assess the precision and accuracy of quantitative proxy-based reconstructions.
Informal Caregiving and Network Turnover Among Older Adults.

Objectives Personal network turnover, a combination of lost and added network contacts, is suggested to affect health as well as moderate access to social support and resources. This paper tests whether the caregiving process is associated with network turnover in later life and whether the process is different for men and women. Method Network turnover was assessed using two waves of personal network data from the National Social Life, Health, and Aging Project. Network contacts were uniquely identified in each wave making it possible to document contact loss and addition. Rates of change were modeled using Poisson regression. Results Respondents transitioning into caregiving lost and added network contacts at higher rates than non-caregivers. Conversely, respondents providing care during both waves and respondents transitioning out of the role saw no significant levels of network turnover. The analysis provided minimal evidence of gender differences. Discussion Findings suggest that the initial shift into the caregiving role is associated with notable personal network change. This is an important consideration given that long-term network instability may lead to poor health and limited access to social resources whereas adaptive network change tends to elicit more positive outcomes.
Identification of Potential Biomarkers and Metabolic Profiling of Serum in Ovarian Cancer Patients Using UPLC/Q-TOF MS

Background/Aims: Ovarian cancer (OC) is a malignant neoplasm of the female reproductive system with a high mortality rate. Identifying useful biomarkers and clarifying the molecular pathogenesis of OC are critical for early diagnosis and treatment. The aim of the study was to identify candidate biomarkers and explore metabolic changes of OC. Methods: A two-stage design was used in our study, with a discovery cohort of OC cases (n = 30) and controls (n = 30) and an independent cohort of cases (n = 17) and controls (n = 18) for validation. The serum metabolic profiling was investigated by ultra-performance liquid chromatography and quadrupole time-of-fight mass spectrometry with positive electrospray ionization. Results: A total of 18 metabolites closely related to OC were identified in the discovery stage, of which 12 were confirmed in the validation cohort. Metabolic pathways in OC related to these biomarkers included fatty acid β-oxidation, phospholipid metabolism, and bile acid metabolism, which are closely related to the proliferation, invasion, and metastasis of cancer cells. Multiple logistic regression analysis of these metabolites showed that 2-piperidinone and 1-heptadecanoylglycerophosphoethanolamine were potential biomarkers of OC, with high sensitivity (96.7%), specificity (66.7%), and area under the receiver operating characteristic curve value (0.894). Conclusion: These findings provide insight into the pathogenesis pathogenesis of OC and may be useful for clinical diagnosis and treatment.
Optimization of injection-molding conditions using genetic algorithm

The quality of a plastic product is determined by the material used, the mold design, and the processing conditions. The objectives of a mold design consist of a mold cooling system, a runner system, and associated gate locations with their types and sizes, and cavity design. Meanwhile, the most important processing conditions during the fill phase are the mold temperature, the melt temperature, and the filling time. In this paper, we use genetic algorithm to optimize molding conditions, which consist of the mold temperature, the melt temperature, and the filling time, based upon the results from flow simulation.
Hardware Conditioned Policies for Multi-Robot Transfer Learning

Deep reinforcement learning could be used to learn dexterous robotic policies but it is challenging to transfer them to new robots with vastly different hardware properties. It is also prohibitively expensive to learn a new policy from scratch for each robot hardware due to the high sample complexity of modern state-of-the-art algorithms. We propose a novel approach called Hardware Conditioned Policies where we train a universal policy conditioned on a vector representation of robot hardware. We considered robots in simulation with varied dynamics, kinematic structure, kinematic lengths and degrees-of-freedom. First, we use the kinematic structure directly as the hardware encoding and show great zero-shot transfer to completely novel robots not seen during training. For robots with lower zero-shot success rate, we also demonstrate that fine-tuning the policy network is significantly more sample-efficient than training a model from scratch. In tasks where knowing the agent dynamics is important for success, we learn an embedding for robot hardware and show that policies conditioned on the encoding of hardware tend to generalize and transfer well. Videos of experiments are available at: https://sites.google. com/view/robot-transfer-hcp.
Are Critical Success Factors Always Valid for Any Case? A Contextual Perspective

The critical success factor (CSF) concept systematically highlights the key areas which management should carefully consider in order to realize its performance goals. By understanding the CSFs for the implementation of a system, an organization can successfully determine the issues that critically affect the process, enabling it to eliminate or avoid any problems that might contribute to its failure. The purpose of this paper is to investigate whether the CSFs presented in the literature are always valid for any case. It reports an exploratory case study which adopted a qualitative methodology to achieve a deep understanding of the CSFs for learning management system (LMS) implementation in Saudi Arabia from the students’ perspective. Having identified these CSFs, it compares them with those reported by other studies in the literature. The results indicate that such CSFs are not similar in all contexts. Studying the change in its context is in fact found to be significant and information system success is determined to be not a purely technical issue but a socio-technical one. Accordingly, the widely recognized CSFs are undeniably beneficial but not sufficient to ensure the success of LMS implementation.
Day and night-time active fire detection over North America using NOAA-16 AVHRR data

Presents an investigation of the applicability of NOAA-16/AVHRR (N-16) satellite data for detecting and mapping active wildfires across North American forest ecosystems. Two fire detection algorithms were developed for application to N-16 day and night-time daily imagery. The algorithms exploit both the multi-spectral and thermal information from the AVHRR daily images. For daytime data collection N-16 provides 3 reflective bands, namely, red, near infrared and short-wave infrared (SWIR), in addition to two thermal brightness temperature bands centred at 10.8 /spl mu/m and 12 /spl mu/m. During nighttime data collection the SWIR band is switched to the thermal brightness temperature band centred at 3.7 /spl mu/m. This band in particular has been extensively used for detecting active fires. The fire algorithms have two major steps: detection of potential fires followed by false fire elimination. The threshold tests developed for fire identification and false fire removal were optimised through a trial-and-error approach using a database of active fire pixels over the whole of North America. The database was generated from a large number of single-daytime and night-time AVHRR scenes, where the fire pixels were identified visually on the images aided by the associated daytime smoke plumes. The SWIR band was found to be sensitive only to large burning fires leading to a noticeable spike in the measured reflectance. However, a serious limitation with the SWIR band is that small burning fires are not easily detectable and quite a number of active fires go undetected. Night detection does not pose such a limitation and has allowed for significantly higher detection rates. Overall night detection provides reasonably good alternative for the reduced sensitivity of the SWIR band. The set of day and night algorithms was used to generate daily active fire maps across North America. Such a combined approach for fire detection leads to an improved detection rate. Selected validation sites in western Canada and the United States, showed reasonable correspondence with the location of fires mapped by the Canadian Forest Service and the USDA Forest Service using conventional means.
Clasificación automática de las vocales en el lenguaje de señas colombiano

Sign language recognition is a highly-complex problem due to the amount of static and dynamic gestures needed to represent such language, especially when it changes from country to country. This article focuses on static recognition of vowels in Colombian Sign Language. A total of 151 images were acquired for each class, and an additional non-vowel class with different scenes was also considered. The object of interest was cut out of the rest of the scene in the captured image by using color information. Subsequently, features were extracted to describe the gesture that corresponds to a vowel or to the class that does not match any vowel. Next, four sets of features were selected. The first one contained all of them; from it, three new sets were generated. The second one was extracted from a subset of features given by the Principal Component Analysis (PCA) algorithm. The third set was obtained by Sequential Feature Selection (SFS) with the FISHER measure. The last set was completed with SFS based on the performance of the K-Nearest Neighbor (KNN) algorithm. Finally, multiple classifiers were tested on each set by cross-validation. Most of the classifiers achieved a performance over 90%, which led to conclude that the proposed method allows an appropriate class distinction.
An Efficient Itemset Representation for Mining Frequent Patterns in Transactional Databases

In this paper we propose very eﬃcient itemset representation for frequent itemset mining from transactional databases. The combinatorial number system is used to uniquely represent frequent k -itemset with just one integer value, for any k ≥ 2. Experiments show that memory requirements can be reduced up to 300 %, especially for very low minimal support thresholds. Further, we exploit combinatorial number schema for representing candidate itemsets during iterative join-based approach. The novel algorithm maintains one-dimensional array rank , starting from k = 2 nd iteration. At the index r of the array, the proposed algorithm stores unique integer representation of the r th candidate in lexicographic order. The rank array provides joining of two candidate k -itemsets to be O (1) instead of O ( k ) operation. Additionally, the rank array provides faster determination which candidates are contained in the given transaction during the support count and test phase. Finally, we believe that itemset ranking by combinatorial number system can be eﬀectively integrated into pattern-growth algorithms, that are state-of-the-art in frequent itemset mining, and additionally improve their performances.
A Social Ecological Approach to Develop a Nutrition Education Program for Preventing Iron Deficiency Anemia in Young Children in Rural Pakistan

ABSTRACT Inappropriate feeding practices puts infants and young children at risk of iron deficiency anemia. Maternal complementary feeding (CF) behavior is determined by influences at various levels, including knowledge and attitude about feeding, inter-personal interaction with family/friends, community norms and support. The aim of this study is to understand the various influences on maternal CF behavior in order to develop a culturally appropriate nutrition education program to improve iron status of children aged 9–24 months. Using a social ecological approach, in-depth interviews with stakeholders revealed restraining factors that prevented behavior change. Culturally appropriate nutrition education messages were developed to address these constraints.
The Pressure Is On – Epiphyte Water-Relations Altered Under Elevated CO2

Vascular epiphytes are a major biomass component of forests across the globe and they contribute to 9% of global vascular plant diversity. To improve our understanding of the whole-plant response of epiphytes to future climate change, we investigated for the first time both individual and combined effects of elevated CO2 (560 ppm) and light on the physiology and growth of two epiphyte species [Tillandsia brachycaulos (CAM) and Phlebodium aureum (C3)] grown for 272 days under controlled conditions. We found that under elevated CO2 the difference in water loss between the light (650 μmol m-2s-1) and shade (130 μmol m-2s-1) treatment was strongly reduced. Stomatal conductance (gs) decreased under elevated CO2, resulting in an approximate 40–45% reduction in water loss over a 24 h day/night period under high light and high CO2 conditions. Under lower light conditions water loss was reduced by approximately 20% for the CAM bromeliad under elevated CO2 and increased by approximately 126% for the C3 fern. Diurnal changes in leaf turgor and water loss rates correlated strong positively under ambient CO2 (400 ppm) and high light conditions. Future predicted increases in atmospheric CO2 are likely to alter plant water-relations in epiphytes, thus reducing the canopy cooling potential of epiphytes to future increases in temperature.
An outline of fusion and sensor combinational methodologies for disparate, sparse multi-sensor networks for detecting icebergs

Regions of extensive marine activity, particularly regions that span hundreds of nautical miles, require wide-area, timely, and reliable remotely sensed information to ensure safe and efficient offshore operations. In some areas, such as the western North Atlantic, this issue is exacerbated for one-third of the year when the region can be frequented by icebergs. This paper reports on development of a framework for "fusing" the various sensor data to provide the most accurate and timely "picture" of the region of interest. Available data includes satellite SAR (synthetic aperture radar) imagery, long-range HF (high frequency) radar, airborne radar, conventional and enhanced marine radar from ships and platforms, and human observation. Work to date has focused primarily on developing performance curves for the various sensors based on empirical data collected over the past two years. This paper presents an overview of that work and the parameters to be optimized in combining data from the disparate sensors.
Controllability issues of robots in singular configurations

Examples are given that modify some oversimplified statements usually made about the motion of robots in singular configurations. A robot may be controlled in an arbitrary direction from a singular configuration if the velocity profiles are shaped in a proper way. The observations on possible motions open a number of questions, since a wider class of motions is possible that at first sight. Hence, the results are of relevance to path programming, to path following, and to controller design. <<ETX>>
5G D2D Networks: Techniques, Challenges, and Future Prospects

The increasing number of mobile users has given impetus to the demand for high data rate proximity services. The fifth-generation (5G) wireless systems promise to improve the existing technology according to the future demands and provide a road map for reliable and resource-efficient solutions. Device-to-device (D2D) communication has been envisioned as an allied technology of 5G wireless systems for providing services that include live data and video sharing. A D2D communication technique opens new horizons of device-centric communications, i.e., exploiting direct D2D links instead of relying solely on cellular links. Offloading traffic from traditional network-centric entities to D2D network enables low computational complexity at the base station besides increasing the network capacity. However, there are several challenges associated with D2D communication. In this paper, we present a survey of the existing methodologies related to aspects such as interference management, network discovery, proximity services, and network security in D2D networks. We conclude by introducing new dimensions with regard to D2D communication and delineate aspects that require further research.
Suicide and Burnout of Physicians

Stressors and health risks in the medical profession are well documented but seldom openly discussed. Very often a “conspiracy of silence” about these stressors exists, and this conspiracy is allowed to continue because of denial and defensiveness. The most important stressors in the medical system result from the treatment of and care for patients. Other stressors are team conflicts, insecurity, lack of autonomy, large workload and increasing criticisms, expectations, and demands from the public. In addition, female doctors complain about the strain they experience in emergency services. They also especially suffer from the role-strain between job stressors and family responsibilities. Signs of these double-stressors can already be seen early in the medical course and mark the whole career of female doctors. Compared to the general population, the overall mortality rate of doctors decreased during the last decade, but is still worse than that of other professionals of comparable education. In particular the suicide rates are high, for males two to three times that of the general population, for females as much as five to six times. This is due to a high proportion of psychiatric diseases, particularly addiction and depression. We must keep in mind, that, despite being “gods in white,” a medical degree does not infer immunity to mental illness, drug addiction, alcoholism, or other self-destructive behaviors.
A Flexible Measurement System for Dielectric Waveguide Characterization at mmW Frequencies

Due to their outstanding transmission behavior of millimeter wave (mmW) signals at high flexibility, low weight and low costs, dielectric waveguides (DWG) represent a convenient technology for future transmission systems and are well suitable for applications like radar, mmW imaging or high speed communication. As different operating conditions require optimized geometries or materials of the DWGs, it is necessary to provide a flexible and robust measurement system to precisely characterize the transmission properties of DWGs with any cross section geometry. To extract the attenuation and phase constants $\alpha$ and $\beta$ a multiline de-embedding technique is used. Measurement results are shown in this paper.
Pregnancy Health Information Use Behavior among Teenage Expectant Mothers: awareness and the Role of Muslim Information Professionals.

Teenage pregnancy has become a health concern of many communities of the World, Muslim communities included. Dissemination, exchange and sharing of women‘s health information is still a riddle in many Muslim societies, and little has been done to explore the use of pregnancy health information among teenage expectant mothers. World widely, adolescent expectant mothers experience low use of pregnancy health information due to young maternal age, low levels of education, poor socioeconomic status, and low levels of self efficacy as a result of teenage pregnancy psychosocial trauma. This phenomenon is insidious as it contributes to their unawareness of various maternal health risks and also keeps them aloof from making informed health decisions and it compromises safe motherhood initiatives to improve maternal health conditions in societies. Little is known on the link between improvement of expectant mothers‘ health conditions and their use of pregnancy health information. The purpose of this paper is to share ideas on the possible role of Muslim information professionals in libraries and information centers on how to improve pregnancy health information use behavior among teenage mothers in our communities, through pregnancy health information motivation and information use skills interventions in order to accelerate safe motherhood initiatives by increasing awareness and knowledge of pregnancy risk factors. The study employed a pretest posttest experimental design to extract information on pregnancy health information use behavior. The findings presented here is from collected data in one of the study site, though still ongoing but it helps to shed lights of the situation. The preliminary results showed that the strong relationship exist between awareness and knowledge of PHI and actual usage of PHI from information sources and PHI resources. The study suggests the need to introduce pregnancy health information motivation and information use skills interventions in order to scale up positive behavior on the use of pregnancy health information for making appropriate and informed health choices. Lastly Muslims information professionals are urged to improve sharing and exchanging ideas as a way to promote and encourage the use of women‘s health information among Muslim communities to raise awareness and knowledge so as to enhance Muslim women‘s health. As Muslim information professionals, we have a duty to participate in creation, processing, organization, and dissemination of health information while incorporating both healthcare providers‘ and Islamic perspectives regarding the need and use of pregnancy health information in our Muslim communities.
Career choices for trauma and orthopaedic surgery: 30 years of surveys

We have surveyed all UK medical graduates in selected years since 1974 to document their career choices, career progression, career destinations and views about various aspects of working in medicine. We have recently summarised our findings for a number of individual specialties (we reference two examples here). This article covers early career choices for trauma and orthopaedic surgery. A fuller version is available on the UK Medical Careers Research Group website at www.uhce. ox.ac. uk/ukmcrg.