Miracle-dz/UniFAR-FTUs huggingface dataset:
Mapping Electronic Transport in Ge Nanowire SBFETs: From Tunneling to NDR

An in-depth discussion of the transport mechanisms in ambipolar Ge nanowire (NW) Schottky barrier (SB) field-effect transistors (SBFETs) embedded in monolithic and crystalline Al-Ge-Al heterostructures is presented. Thereto, detailed bias spectroscopy in the temperature regime between T=77.5K and 400 K was conducted. In conjunction with the obtained activation energy maps, a highly transparent contact for holes due to charge carrier injection saturation by Fermi level pinning close to the valence band and gate induced thinning of the SB width was observed. In contrast, the thermionic-and field-emission mechanism limits the overall electron conduction, indicating a distinct SB for electrons. In this regime, nanoscaled Ge distinctly differs from its bulk counterpart and delivers a strong and reproducible negative differential resistance (NDR) at room-temperature (RT) followed by a sudden current increase indicating the onset of impact ionization above a specific threshold electric field.
Las competencias de los graduados y su evaluación desde la perspectiva de los empleadores

espanolEl proposito de este articulo es estudiar las percepciones de los empleadores acerca de las competencias que deberian tener los graduados universitarios en el ambito laboral y de la contribucion de la evaluacion a su desarrollo. Desde un enfoque metodologico cualitativo y mediante cuestionario abierto, se ha recabado informacion de empleadores de Educacion Primaria, Farmacia e Ingenieria sobre las siguientes cuestiones: competencias que deberian tener los graduados, instrumentos y criterios de evaluacion que utilizan en sus procesos de seleccion y valoracion sobre el aprendizaje y la evaluacion de competencias en la universidad. Los resultados permiten contrastar percepciones ofrecidas desde los tres sectores investigados. Finalmente, presentamos una reflexion critica que profundiza en la complejidad del enfoque de competencias y la necesidad de adaptar los sistemas de evaluacion. Se aportan sugerencias para estrechar la relacion con el mundo laboral, incrementar la empleabilidad y mejorar la calidad de la ensenanza universitaria. EnglishThe purpose of this article is to show the employer's perspective regarding the competences required of college graduates, from different professional sectors and the contribution of evaluation systems to its development and assessment. From a qualitative methodological approach, an open questionnaire has been applied in order to gather information from employers of Primary Education, Pharmacy and Engineering on the following issues: competences that graduates should have; instruments and evaluation criteria used in their selection processes and, learning strategies and assessment systems used at the university. The results allow us contrasting perceptions offered from the three sectors investigated. Finally, we present a critical reflection that explores the complexity of the competencies approach and the need to adapt the evaluation systems to this new scenario. Suggestions to strengthen the relationship with the labor market, increasing employability and improving the quality of university education are provided.
Approximate arithmetic aware training for stochastic computing neural networks

Deploying modern neural networks on resource-constrained edge devices requires a series of optimizations to prepare them for production. These optimizations typically involve pruning, quantization, and fixed-point conversion to compress the model size and improve energy efficiency. While these optimizations are generally sufficient for most edge devices, there is potential for further improving energy efficiency by leveraging special-purpose hardware and unconventional computing paradigms. In this work, we investigate stochastic computing neural networks and their impact on quantization and overall performance with respect to weight distributions. When arithmetic operations such as addition and multiplication are performed by stochastic computing hardware, the arithmetic error may increase significantly, resulting in reduced overall accuracy. To bridge the accuracy gap between a fixed-point model and its stochastic computing implementation, we propose a new approximate arithmetic aware training method. We demonstrate the effectiveness of our approach by implementing the LeNet-5 convolutional neural network on an FPGA. Our experimental results show a negligible accuracy degradation of only 0.01% compared to the floating-point outcome, while achieving a significant 27x speedup and 33x improvement in energy efficiency compared to other FPGA implementations. Moreover, the proposed method increases the likelihood of selecting optimum LFSR seeds for SC systems.
TCP Congestion Control Performance Issues in Non-Standalone 5G NR Networks

The ongoing deployment of 5G networks and the heterogeneity of carrier aggregation in 4G networks have resulted in vast differences of cellular network performance across different locations. Especially for mobile users, such fluctuation in performance based on location can result in a highly degraded user experience. The problem is compounded by the fact that popular TCP congestion control variants, such as CUBIC and BBR, can be slow to adjust their congestion window when network conditions change rapidly.In this paper, we analyze the extent to which the network conditions can change over brief periods of time for mobile users by performing repeated drive tests on a route with a diverse network coverage. We show that due to differences in the availability of different 4G and 5G carriers, the total carrier bandwidth available to a user can change multiple times in a period of a few seconds, which results in major changes of achievable throughput. As TCP can be slow in adjusting its congestion window, this can result in either low bandwidth utilization or high delays due to bufferbloat. We propose that for a more efficient bandwidth utilization, the information about total carrier bandwidth could be used in TCP congestion control.
Pulse Pressure is Sex-Specifically Associated with the Ratio of Diastolic and Systolic Arterial Pressure in Healthy Children, and Differently During Night Versus Daytime Recordings

Noninvasive blood pressure recordings typically focus on systolic blood pressure (SBP) and diastolic pressure (DBP). Derived metrics are often analyzed, e.g. pulse pressure (PP), defined as SBP minus DBP. As the metric PP is not unique, we introduced the PP companion (PPC), calculated using the Pythagorean theorem. PPC is associated with mean arterial pressure (MAP). Another mathematical construct frequently used in hemodynamic studies refers to the ratio of DBP and SBP, denoted as Prat. PP and Prat share the same companion (C). The association between PratC and MAP, as well as the connection between PP and Prat has not been studied in healthy children. We analyzed a large set of daytime (DT) and nighttime (NT) data (N=949, age 5 to 16 years, including 485 girls), published in the literature. Average PP increases with age (in 0.5 year increments), while Prat decreases. Prat vs PP yields R2>0.985 for both DT and NT data, when stratified for boys and girls. PPC is significantly lower (P<0.0001) during the night for both sexes. We conclude that Prat carries no substantial incremental value beyond PP, in contrast to PPC which points to DT/NT, age-dependent and sex-specific differences in these children.Clinical Relevance— Various derived metrics based on blood pressure have been introduced in hemodynamic studies, but not all of them are fully independent. The diastolic to systolic pressure ratio in healthy children is inversely associated with pulse pressure, showing partial sex-specific overlap, but substantial daytime versus night differences.
Development of a rabbit model of Adenosine triphosphate-induced monocular retinal degeneration for optimization of retinal prostheses*

Optimization of retinal prostheses requires preclinical animal models that mimic features of human retinal disease, have appropriate eye sizes to accommodate implantable arrays, and provide options for unilateral degeneration so as to enable a contralateral, within-animal control eye. In absence of a suitable non-human primate model and shortcomings of our previous feline model generated through intravitreal injections of Adenosine Triphosphate (ATP), we aimed in the present study to develop an ATP induced degeneration model in the rabbit. Six normally sighted Dutch rabbits were monocularly blinded with this technique. Subsequent retinal degeneration was assessed with optical coherence tomography, electroretinography, and histological assays. Overall, there was a 42% and 26% reduction in a-wave and oscillatory potential amplitudes in the electroretinograms respectively, along with a global decrease in retinal thickness, with increased variability. Qualitative inspection also revealed that there were variable levels of retinal degeneration and remodeling both within and between treated eyes, mimicking the disease heterogeneity observed in retinitis pigmentosa. These findings confirm that ATP can be utilized to unilaterally induce blinding in rabbits and, potentially present an ideal model for future cortical recording experiments aimed at optimizing vision restoration strategies.Clinical Relevance— A rapid, unilaterally induced model of retinal degeneration in an animal with low binocular overlap and large eyes will allow for clinically valid recordings of downstream cortical activity following retinal stimulation. Such a model would be highly beneficial for the optimization of clinically appropriate vision restoration approaches.
Adjusting Point Size to Facilitate More Accurate Correlation Perception in Scatterplots

Viewers consistently underestimate correlation in positively correlated scatterplots. We use a novel data point size manipulation to correct for this bias. In a high-powered and fully reproducible study, we demonstrate that decreasing the size of a point on a scatterplot as a function of its distance from the regression line is able to correct for a systematic perceptual bias long present in the literature. We recommend the implementation of our technique when designing scatterplots that aim to communicate positive correlations.
Wrench Estimation of Modular Manipulator with External Actuation and Joint Locking

This paper proposes an external wrench estimation method for modular manipulators, where each link module is driven with external actuation (e.g., rotors, thrusters) and inter-module joints can be locked to increase end-effector stiffness or workforce of the manipulator. For such systems, the commonly-used momentum-based observer (MBO [1]) is not suitable due to the presence of unknown joint locking (JL) torque and also the degeneracy of Jacobian transpose relation with the system degree-of-freedom (DOF) becoming less than six with the joint locking. To overcome this, we propose two novel external wrench estimation algorithms: a distributed algorithm based on recursive Newton-Euler dynamics and a centralized algorithm based on D'Alembert's principle, both using an F/T (force/torque) sensor at the base. Experiments are conducted to demonstrate the effectiveness of the proposed algorithms.
Comparative Analysis of the Reported Animal-Vehicle Collisions Data and Carcass Removal Data for Hotspot Identification

Two common types of animal-vehicle collision data (reported animal-vehicle collision (AVC) data and carcass removal data) are usually recorded by transportation management agencies. Previous studies have found that these two datasets often demonstrate different characteristics. To accurately identify the higher-risk animal-vehicle collision sites, this study compared the differences in hotspot identification and the effect of explanation variables between carcass removal and reported AVCs. To complete the objective, both the Negative Binomial (NB) model and the generalized Negative Binomial (GNB) are applied in calculating the Empirical Bayesian (EB) estimates using the animal collision data collected on ten highways in Washington State. The important findings can be summarized as follows. (1) The explanatory variables have different effects on the occurrence of carcass removal data and reported AVC data. (2) The ranking results from EB estimates when using carcass removal data and reported AVC data differ significantly. (3) The results of hotspot identification are different between carcass removal data and reported AVC data. However, the ranking results of GNB models are better than those of NB models in terms of consistency. Thus, transportation management agencies should be cautious when using either carcass removal data or reported AVC data to identify hotspots.
Why Was Benghazi "Saved," but Sinjar Allowed to Be Lost?: New Failures of Genocide Prevention, 2007–2015

In this article, I examine legal, political, and cultural reasons behind the genocides in Iraq and Syria of 2007–2015, that decimated the Yezidi communities of Sinjar or Shingal (Şengal/Şingal/Şingar). It is typically argued that failures to prevent genocide occur due to imaginative deficits or fear of a military quagmire. However, I show that atrocities are quickly recognized and sanctioned in some cases, and that substantial resources in terms of international support, military assets, and political rhetoric have been generated in several cases in which groups were less threatened than the Yezidis. To explain the disparate responses to claims of imminent persecution or massacre, I develop the theory of the "Reverse CNN Effect," in which some tragedies do not receive the requisite attention of the mass media to mobilize action. The phenomenon extends beyond the media to the resolutions and reports of the United Nations and, at times, those of the US government.
Investigation of the Radiative Heat Transfer of An Axisymmetric Nozzle Based on Null-collision Monte Carlo Method

Accurate simulation of radiative heat transfer inside the nozzle can help extend the nozzle's lifetime and optimize the design of thermal protection structures. Hence, this article employs the null-collision reverse Monte Carlo method (NC-RMC) to establish the radiative heat transfer model for a typical cylindrical nozzle, where line-by-line (LBL) calculations combined with K-distribution method and Mie scattering theory are utilized respectively to analyze gaseous and particulate radiative properties. A fast localization algorithm in axisymmetric unstructured mesh is also developed to trace the energy bundles. The above models have been validated by several tests and then executed to investigate the effects of particulate scattering on the distribution of negative radiative source terms. The results show that with the increase of the particulate diameter, the negative radiative source terms on the centerline decrease, and the particulate scattering effects almost remain constant when the particulate diameter is smaller than 1.0 micrometer.
C O N T E N T S

The significant role of telecommunication technology in the economic sector has caused increasing competition in the mobile service market. As for business survival, a mobile service package is now required to become even more innovative than before. Customer satisfaction plays a vital role in mobile services and it will impact on brand switching among mobile service users. This study aimed to examine factors that influence customer satisfaction which will subsequently affect the brand switching intention of customers. Among the factors studied were service quality, service pricing, customer service and value-added service. A total of 200 students from a local private university were recruited using the convenience sampling technique based on self-administered questionnaires. The collected data was then analysed using PLS-SEM. The findings show that all the factors tested were found to have a positive impact on customer satisfaction except service quality and value-added service. Customer satisfaction was also found to have a negative effect on brand switching of customers of mobile service. The findings of this research have provided useful information to mobile service providers in planning their marketing strategy. They have to be more innovative in their efforts to meet the growing and different needs of customers and retain them from switching to opponent mobile service brands in the market.
Morph-Specific Patterns Of Reproductive Senescence: Morph-Specific Patterns Of Reproductive Senescence: Connections To Discrete Reproductive Strategies Connections To Discrete Reproductive Strategies

: How reproductive strategies contribute to patterns of senescence in natural populations remains contentious. We studied reproductive senescence in the dimorphic white-throated sparrow, an excellent species for exploring this issue. Within both sexes the morphs use distinct reproductive strategies, and disassortative pairing by morph results in pair types with distinct parental systems. White morph birds are more colorful and aggressive than tan counterparts, and white males compete for extrapair matings, whereas tan males are more parental. Tan males and white females share parental care equally, whereas white males provide little parental support to tan females. We found morph-speci ﬁ c patterns of reproductive senescence in both sexes. White males exhibited greater reproductive senescence than tan males. This result likely re ﬂ ects the dif ﬁ culty of sustaining a highly competitive reproductive strategy as aging progresses rather than high physiological costs of competitiveness, since white males were also long-lived. Moreover, morph was not consistently related to reproductive senescence across the sexes, arguing against especially high costs of the traits associated with white morph identity. Rather, tan females exhibited earlier reproductive senescence than white females and were short-lived, perhaps re ﬂ ecting the challenges of unsupported motherhood. Results underscore the importance of social dynamics in determining patterns of reproductive senescence.
ELECTRONIC RUBRIC: EVALUATION TOOL IN THE ASSESSMENT PROCESS IN VOCATIONAL EDUCATION

Integrating technology in the assessment process facilitates the overall education process, both for teachers, students, and educational institutions. In this research, we analysed the use of electronic rubric (e-rubric) to assess learning process. In this research, electronic rubric was applied in Vocational Education in the implementation of Serving Procedure practicum courses. In this study used a qualitative approach to lecture and students. The survey used to obtain information using the form Use Questionary which Likert scale consists of four components, namely the quality of usefulness, satisfaction, ease of use and ease of learning given to the two lecturers, and the questionnaire was given to 14 students to collect their perceptions regarding the use e-rubric on practicum ratings. The results showed that the performance assessment instrument in the form of electronic rubric in the Serving Procedure course could provide convenience to lecturers in measuring students' skills in practicum activities. Through satisfaction survey, the research concluded that electronic rubric is a resource that facilitates assessment for students as participants in the assessment process. Students tend to be satisfied with the use of electronic rubric in the assessment process. Students tend to be satisfied with the use of electronic rubric in the assessment, a student can monitor the process and the progress of competence to be achieved and how to fix it when it has not been achieved competence. Electronic rubric to describe the specific characteristics of the learning outcomes achieved by students (products and tasks) as well as the level of performance that must be achieved by the students.
Do More with Less: Single-Model, Multi-Goal Architectures for Resource-Constrained Robots

Deep learning methods are widely used in robotic applications. By learning from prior experience, the robot can abstract knowledge of the environment, and use this knowledge to accomplish different goals, such as object search, frontier exploration, or scene understanding, with a smaller amount of resources than might be needed without that knowledge. Most existing methods typically require a significant amount of sensing, which in turn has significant costs in terms of power consumption for acquisition and processing, and typically focus on models that are tuned for each specific goal, leading to the need to train, store and run each one separately. These issues are particularly important in a resource-constrained setting, such as with small-scale robots or during long-duration missions. We propose a single, multi-task deep learning architecture that takes advantage of the structure of the partial environment to predict different abstractions of the environment (thus reducing the need for rich sensing), and to leverage these predictions to simultaneously achieve different high-level goals (thus sharing computation between goals). As an example application of the proposed architecture, we consider the specific example of a robot equipped with a 2-D laser scanner and an object detector, tasked with searching for an object (such as an exit) in a residential building while constructing a topological map that can be used for future missions. The prior knowledge of the environment is encoded using a U-Net deep network architecture. In this context, our work leads to an object search algorithm that is complete, and that outperforms a more traditional frontier-based approach. The topological map we produce uses scene trees to qualitatively represent the environment as a graph at a fraction of the cost of existing SLAM-based solutions. Our results demonstrate that it is possible to extract multi-task semantic information that is useful for navigation and mapping directly from bare-bone, non-semantic measurements.
Social Network Emotional Marketing Inﬂuence Model of Consumers’ Purchase Behavior

: With the deepening application of Internet technology, social network emotional marketing has become a new way of sustainability marketing. However, most of the existing emotional marketing research belongs to the ﬁeld of qualitative research, and there is a lack of data analysis and empirical research between social network emotional marketing and consumers’ purchase behavior. In this paper, ﬁrstly the inﬂuencing factors of consumers’ purchase behavior are extracted from a massive social network emotional marketing data set, and the Delphi method is adopted to interview experts to revise and improve the inﬂuencing factors. Then, a model simulating the inﬂuence of social network emotional marketing on consumers’ purchasing behavior is constructed. The proposed model explores the mechanism of the inﬂuence of social network emotional marketing on consumers’ purchase behavior through trust, attachment and other psychological factors from the perspective of emotion. Finally, a questionnaire is used to obtain survey data, and statistical methods are used to analyze the relevant data, so as to verify the correctness of the proposed model and related research hypothesis.