Output Patterns Research Articles

Phenotypic relationship and repeatability of methane emissions and performance traits in beef cattle using a GreenFeed system.

Rumen methanogenesis results in the loss of 6% to 10% of gross energy intake in cattle and globally is the single most significant source of anthropogenic methane (CH4) emissions. The purpose of this study was to analyze greenhouse gas traits recorded in a commercial feedlot unit to gain an understanding into the relationships between greenhouse gas traits and production traits. Methane and carbon dioxide (CO2) data recorded via multiple GreenFeed Emission Monitoring (GEM), systems as well as feed intake, live weight, ultrasound scanning data, and slaughter data were available on 1,099 animals destined for beef production, of which 648 were steers, 361 were heifers, and 90 were bulls. Phenotypic relationships between GEM emission measurements with feed intake, weight traits, muscle ultrasound data, and carcass traits were estimated. Utilization of GEM systems, daily patterns of methane output, and repeatability of GEM system measurements across averaging periods were also assessed. Methane concentrations varied with visit number, duration, and time of day of visit to the GEM system. Mean CH4 and CO2 varied between sex, with mean CH4 of 256.1 g/day ± 64.23 for steers, 234.7 g/day ± 59.46 for heifers, and 156.9 g/day ± 55.98 for young bulls. A 10-d average period of GEM system measurements were required for steers and heifers to achieve a minimum repeatability of 0.60; however, higher levels of repeatability were observed in animals that attended the GEM system more frequently. In contrast, CO2 emissions reached repeatability estimates >0.6 for steers and heifers in all averaging periods greater than 2-d, suggesting that cattle have a moderately consistent CO2 emission pattern across time periods. Animals with heavier bodyweights were observed to have higher levels of CH4 (correlation = 0.30) and CO2 production (correlation = 0.61), and when assessing direct methane, higher levels of dry matter intake were associated with higher methane output (correlation = 0.31). Results suggest that reducing CH4 can have a negative impact on growth and body composition of cattle. Methane ratio traits, such as methane yield and intensity were also evaluated, and while easy to understand and compare across populations, ratio traits are undesirable in animal breeding, due to the unpredictable level of response. Methane adjusted for dry matter intake and liveweight (Residual CH4) should be considered as an alternative emission trait when selecting for reduced emissions within breeding goals.

Quantitative Measurement of the Pressure and Shear Stress Acting on the Body of a Wheelchair User Using a Wearable Sheet-Type Sensor: A Preliminary Study.

To provide a safer sitting environment for wheelchair users, it is important to quantitatively measure the forces acting on the contact surface between the seat and the person in the wheelchair. In addition to the pressure acting on the buttocks, shear forces have received particular attention in recent years; however, measuring shear force is more difficult than measuring pressure. To obtain this measurement, a thin and flexible sensor that can be used in a natural state on a wheelchair is needed. Therefore, we constructed a measurement system using our previously developed wearable sheet-type sensor (0.9 mm thick). In this study, preliminary tests were conducted using human dummies before testing on humans. Sensors were placed in four locations on the humanoid dummy’s back and buttocks, and the electric wheelchair was tilted and reclined five times each. The results showed that the sensor output pattern was reproducible and valid enough to proceed to the next step. However, the shear force in the internal and external directions was greater than expected, which indicates that the equipment and testing methods must be reviewed. On the basis of the results obtained in this preliminary study, preparations will be made for testing on human subjects.

Analysis on the Particularity of Higher Education Subject Development under the Background of Artificial Intelligence

Subject development plays a crucial role in higher education (HE), improving student academic performance. The HE continuously requires conceptual and empirical development to deliver valuable content to the students. The subject reforms offer quality, accessibility, affordability, accountability, and equity to accomplish continual learning. The changes in higher education subjects require a continuous assessment to understand the relationship between the reform and student performance. The subject development quality is evaluated using machine learning (ML) and artificial intelligence (AI) techniques. The existing researchers use intelligent techniques to identify student academic performance. However, the exact relationship between student performance and subject changes fails to address. Therefore, higher education learning (HEL) requires improvement to manage the Higher Education Subject Development (HESD). To achieve the research goal, AdaBoost Adaptive-Bidirectional Associative Memory (AA-BAM) network is introduced in this work. The network model uses the Hebbian supervised learning (HSL) process to create the training model. The learning process has a network parameter updating procedure that reduces the total error and deviation between the academic details. In addition, the neural model uses the memory cell that stores every processing information that recalls the output patterns with maximum accuracy. The output pattern identifies the student’s academic performance, which helps to analyze the quality of the subject development in institutions. The created system ensures 98.78% accuracy, showing that subject development correlates highly with student academic performance.

Neural population clocks: Encoding time in dynamic patterns of neural activity.

The ability to predict and prepare for near- and far-future events is among the most fundamental computations the brain performs. Because of the importance of time for prediction and sensorimotor processing, the brain has evolved multiple mechanisms to tell and encode time across scales ranging from microseconds to days and beyond. Converging experimental and computational data indicate that, on the scale of seconds, timing relies on diverse neural mechanisms distributed across different brain areas. Among the different encoding mechanisms on the scale of seconds, we distinguish between neural population clocks and ramping activity as distinct strategies to encode time. One instance of neural population clocks, neural sequences, represents in some ways an optimal and flexible dynamic regime for the encoding of time. Specifically, neural sequences comprise a high-dimensional representation that can be used by downstream areas to flexibly generate arbitrarily simple and complex output patterns using biologically plausible learning rules. We propose that high-level integration areas may use high-dimensional dynamics such as neural sequences to encode time, providing downstream areas information to build low-dimensional ramp-like activity that can drive movements and temporal expectation. (PsycInfo Database Record (c) 2022 APA, all rights reserved).

SLMGAN: Single-layer metasurface design with symmetrical free-form patterns using generative adversarial networks

The metasurfaces offering the required spectral responses have ushered in a revolution of manipulating the light in a prescribed manner. A single-layer metasurface design is more appealing than a multi-layer one due to the fabrication complexities. To date, various research groups have explored on architected metasurfaces with general shapes of cubes, crosses, or octothorpes, while a few works utilized evolutionary algorithms to search for metasurfaces with free-form patterns, which relied on the quality of the initial guess. In this paper, a solution is presented to replace the intuition-based approach with generative adversarial networks. The constructed generative networks mathematically formulate the virtual mappings between the pairs of optical spectra and symmetrical patterns with user-defined geometric structures. When fed a time sequence of spectra, the designed networks assimilate the physical property and generate on-demand patterns to match the desired responses. The output patterns are proved to yield matching optical responses with an average accuracy of 0.9. Generative Adversarial Networks are firstly applied to single-layer metasurface designs with symmetrical free-form patterns for desired optical spectra in an inverse-design system.

Distributed information encoding and decoding using self-organized spatial patterns

SummaryDynamical systems often generate distinct outputs according to different initial conditions, and one can infer the corresponding input configuration given an output. This property captures the essence of information encoding and decoding. Here, we demonstrate the use of self-organized patterns that generate high-dimensional outputs, combined with machine learning, to achieve distributed information encoding and decoding. Our approach exploits a critical property of many natural pattern-formation systems: in repeated realizations, each initial configuration generates similar but not identical output patterns due to randomness in the patterning process. However, for sufficiently small randomness, different groups of patterns that arise from different initial configurations can be distinguished from one another. Modulating the pattern-generation and machine learning model training can tune the tradeoff between encoding capacity and security. We further show that this strategy is scalable by implementing the encoding and decoding of all characters of the standard English keyboard.

Compact cyclic fiber three-mode converter based on mechanical fiber grating.

In this Letter, a compact cyclic mode converter (CMC) based on a mechanical fiber grating is proposed and fabricated to eliminate differential mode group delay and mode-dependent loss in the mode division multiplexing (MDM) transmission system. The proposed CMC can realize cyclical interchange of any input mode among the LP01/LP11a/LP11b modes, which requires only one mechanical grating. The mode conversion is evaluated by observing the mode field patterns of the fiber output. The experimental results prove that the introduction of CMC does not significantly degrade the transmission performance of the photonic lanterns back-to-back system. The insertion loss and the average cross talk of the whole system are lower than 5 dB and -11.3 dB, respectively. The proposed CMC provides a new method for reducing link damage in the MDM transmission system.

Impacts of natural and human factors on water-related ecosystem services in the Dongting Lake Basin

Correctly identifying and understanding the drivers of ecosystem change and their impacts on ecosystem services (ESs) could provide comprehensive supporting information for ecological governance decisions. This study aimed to identify the key drivers and influencers of natural and human factors on water-related ecosystem services (WESs) in three aspects: spatial heterogeneity contribution, driving relationships, and constraining relationships. The study area included the Dongting Lake Basin, which was divided into 2816 sub-basins as the spatial unit. The WESs of water production, soil conservation, and water purification (output nitrogen) from 2000 to 2020 were quantified, and the impact of environmental factors on WESs and ES enhancement potential were assessed. The results showed that: (1) From 2000 to 2020, the three WESs increased in varying degrees; water production, soil conservation, and nitrogen export increased by 27.60%, 43.20%, and 1.50%, respectively. (2) Precipitation (PRE), slope (Slope), and percentage of ecological land (ELP) were the dominant factors influencing the spatial heterogeneity pattern of water production, soil conservation, and nitrogen output, respectively; PRE, Slope, and ELP had evident nonlinear relationships with the WESs and displayed segmental regression relationship characteristics. (3) Natural and human factors had significant constraining effects on the WESs, even though the driving effects were not significant. (4) Potential measurement results that integrate the driving and limiting effects of factors showed significant heterogeneity, which allows for the screening of efficient ES enhancement measures and locating the implementation space. Therefore, comprehensively considering the effects of multiple drivers and obtaining a multilateral understanding of the impact of the driving factors on ESs will help refine and optimize environmental management decisions.

Near-Infrared Speckle-Illumination Imaging Based on a Multidimensionally Disordered Fiber Laser

Speckle illumination is extensively applied in various imaging scenarios due to its advantages in enhancing the performance of imaging. Generally, the existing speckle-illumination methods are mainly based on external spatial modulation of light through a rotating diffuser or spatial light modulator. Both the lighting efficiency and the system's compactness are limited for these conventional external modulation methods, due to their free-space light coupling and insertion or diffraction loss. Here, a multimode fiber laser with self-reconfigurable speckle illumination is proposed and realized, benefiting from the temporal-spectral randomness of a homemade coherent random-fiber laser and the spectral-sensitive output pattern of an out-coupling multimode fiber. Output characteristics in the spectral and spatial domain of the proposed laser are analyzed and show dynamically varying speckles within a moderate bandwidth. These features pave efficient ways for superresolution imaging through an opaque scattering medium as well as ghost imaging, which is realized and demonstrated based on the lighting of the proposed laser.

Technological Capabilities in Organizational Innovation

Because technological innovation plays a key role in influencing firms’ longevity and performance, the question of why do firms differ in their ability to develop successful inventions became a central topic in the fields of management, strategy, and organizational theory. We contribute to answering it by theorizing the influence a firm’s technological capability strategy, which includes choices about the breadth of an overall capability portfolio and fungibility of individual technologies, has on its inventive success as measured by the quantity of developed inventions and the propensity to build technological breakthroughs. To test our predictions, we leveraged three decades of patenting histories of over two thousand firms, which together spanned nearly three hundred industries. Our empirical approach enabled us to characterize patterns of firm-level inventive outputs and technological capabilities at a highly detailed level while allowing for variation across time. Our results showed that firms with broad capability portfolios and highly general-purpose individual technologies outpace those with opposite capability strategies in the quantity of developed inventions. However, we also found that the capability strategy that fosters the highest overall inventive output does not translate into production of breakthroughs. Our analyses showed that firms that build narrow capability portfolios, but develop highly general-purpose capabilities within this narrow range, are the ones with the highest chances of producing breakthrough inventions. Our findings contribute to scholarship on corporate innovation and literature on firm capabilities.

Measuring Pattern Separation in Hippocampus by in Situ Hybridization.

Distinguishing different contexts is thought to involve a form of pattern separation that minimizes overlap between neural ensembles representing similar experiences. Theoretical models suggest that the dentate gyrus (DG) segregates cortical input patterns before relaying its discriminated output patterns to the CA3 hippocampal field. This suggests that the evaluation of neural ensembles in DG and CA3 could be an important means to investigate the process of pattern separation. In the past, measurement of entorhinal cortex (EC), DG, and CA3 ensembles was largely dependent upon in vivo electrophysiological recording, which is technically difficult. This protocol provides a method to instead measure pattern separation by a molecular method that provides direct spatial resolution at the cellular level. © 2022 Wiley Periodicals LLC. Basic Protocol: Measuring pattern separation by molecular methods.

Evaluation of Spatiotemporal Patterns of the Spinal Muscle Coordination Output during Walking in the Exoskeleton.

Recent advances in the performance and evaluation of walking in exoskeletons use various assessments based on kinematic/kinetic measurements. While such variables provide general characteristics of gait performance, only limited conclusions can be made about the neural control strategies. Moreover, some kinematic or kinetic parameters are a consequence of the control implemented on the exoskeleton. Therefore, standard indicators based on kinematic variables have limitations and need to be complemented by performance measures of muscle coordination and control strategy. Knowledge about what happens at the spinal cord output level might also be critical for rehabilitation since an abnormal spatiotemporal integration of activity in specific spinal segments may result in a risk for abnormalities in gait recovery. Here we present the PEPATO software, which is a benchmarking solution to assess changes in the spinal locomotor output during walking in the exoskeleton with respect to reference data on normal walking. In particular, functional and structural changes at the spinal cord level can be mapped into muscle synergies and spinal maps of motoneuron activity. A user-friendly software interface guides the user through several data processing steps leading to a set of performance indicators as output. We present an example of the usage of this software for evaluating walking in an unloading exoskeleton that allows a person to step in simulated reduced (the Moon’s) gravity. By analyzing the EMG activity from lower limb muscles, the algorithms detected several performance indicators demonstrating differential adaptation (shifts in the center of activity, prolonged activation) of specific muscle activation modules and spinal motor pools and increased coactivation of lumbar and sacral segments. The software is integrated at EUROBENCH facilities to benchmark the performance of walking in the exoskeleton from the point of view of changes in the spinal locomotor output.

Disruptive innovation and spatial inequality

ABSTRACT Although technological change is widely credited as driving the last 200 years of economic growth, its role in shaping patterns of inequality remains under-explored. Drawing parallels across two industrial revolutions in the United States, this paper provides new evidence of a relationship between highly disruptive forms of innovation and spatial inequality. Using the universe of patents granted between 1920 and 2010 by the US Patent and Trademark Office (USPTO), we identify disruptive innovations through their rapid growth, complementarity with other innovations and widespread use. We then assign more and less disruptive innovations to subnational regions in the geography of the United States. We document three findings that are new to the literature. First, disruptive innovations exhibit distinctive spatial clustering in phases understood to be those in which industrial revolutions reshape the economy; they are increasingly dispersed in other periods. Second, we discover that the ranks of locations that capture the most disruptive innovation are relatively unstable across industrial revolutions. Third, regression estimates suggest a role for disruptive innovation in regulating overall patterns of spatial output and income inequality.

Dynamic mixing models and analysis of the mixing processes for an oxidation ditch and an aeration tank.

A one-dimensional longitudinal mixing model for an oxidation ditch with a moving symmetrical boundary and a series model for a symmetric aeration mixing unit of an aeration tank were developed in this study to analyze their mixing processes. The analysis of these models showed that the mixing process in the oxidation ditch tended to that of a continuous stirred tank reactor (CSTR) in a mode of circulation flow and dispersion; however, the mixing in the aeration tank tended to that of a CSTR in a mode of dispersion. The tracer output patterns and complete mixing times of the oxidation ditch and aeration tank with treatment capacities of 1000-50,000 m3 /d and hydraulic retention time 12.0h were evaluated. The complete mixing time increased from 7.5min to 128.5min for the aeration tank with an increase in volume; and the oxidation ditch with same complete mixing time as that of the aeration tank was obtained. The complete mixing time for the oxidation ditch can be changed in a wider range, for matching the time scale of biochemical degradation of organic pollutants. PRACTITIONER POINTS: Mixing model of an oxidation ditch and an aeration tank were built. Mixing in oxidation ditch tends to that of CSTR in a mode of circulation flow and dispersion. Mixing in an aeration tank is in accordance with advection diffusion and tends to that of CSTR as its Peclet number is large. Complete mixing time for an oxidation ditch can be changed in a wider range.

Soft Multi-Directional Force Sensor for Underwater Robotic Application.

Tactile information is crucial for recognizing physical interactions, manipulation of an object, and motion planning for a robotic gripper; however, concurrent tactile technologies have certain limitations over directional force sensing. In particular, they are expensive, difficult to fabricate, and mostly unsuitable for underwater use. Here, we present a facile and cost-effective synthesis technique of a flexible multi-directional force sensing system, which is also favorable to be utilized in underwater environments. We made use of four flex sensors within a silicone-made hemispherical shell structure. Each sensor was placed 90 apart and aligned with the curve of the hemispherical shape. If the force is applied on the top of the hemisphere, all the flex sensors would bend uniformly and yield nearly identical readings. When force is applied from a different direction, a set of flex sensors would characterize distinctive output patterns to localize the point of contact as well as the direction and magnitude of the force. The deformation of the fabricated soft sensor due to applied force was simulated numerically and compared with the experimental results. The fabricated sensor was experimentally calibrated and tested for characterization including an underwater demonstration. This study would widen the scope of identification of multi-directional force sensing, especially for underwater soft robotic applications.

Making Artificial Brains: Components, Topology, and Optimization.

Making Artificial Brains: Components, Topology, and Optimization.

PEMBINAAN KOMPETENSI DOSEN UNTUK PENINGKATAN PRESTASI MAHASISWA PADA SEKOLAH TINGGI ILMU TARBIYAH AL-HILAL SIGLI

The competence of lecturers as educators has a very good position, which has a direct influence on the learning process, quality of graduates and competitive output patterns. The purpose of this study was to determine the program of coaching, implementation of coaching, and competency development of lecturers to improve student achievement at the Tarbiyah Al-Hilal Sigli College. This research was conducted at STIT Al-Hilal Sigli. The resource persons consisted of the Chairperson, lecturers and students of STIT Al-Hilal Sigli. This research is descriptive qualitative. The results of the study indicate that the long-term lecturer competency development program includes syllabus development, evaluation of lecturer performance, lecturer development that is relevant to the subjects taught through. The development of lecturer competence, especially by sending lecturers to continue their education to the Masters and Doctoral levels in various universities. The implementation of lecturer competency development is not only focused on further education, but is also carried out through activities by inviting tutors from outside, holding scientific seminars and discussions, comparative studies and partnerships, which are carried out with several Islamic universities, such as IAIN on the Java island. The existence of knowledge that is built positively can add to the experience of lecturers, thereby increasing their competence as teaching staff and educators. Obstacles in developing lecturer competencies, limited student programs, there are still many lecturers who do not master foreign languages, especially Arabic and English.

Effect of partial distinguishability on quantum supremacy in Gaussian Boson sampling

Gaussian boson sampling (GBS) allows for a way to demonstrate quantum supremacy with the relatively modest experimental resources of squeezed light sources, linear optics, and photon detection. In a realistic experimental setting, numerous effects can modify the complexity of the sampling, in particular loss, partial distinguishability of the photons, and the use of threshold detectors rather than photon counting detectors. In this paper, we investigate GBS with partial distinguishability using an approach based on virtual modes and indistinguishability efficiency. We develop a model using these concepts and derive the probabilities of measuring a specific output pattern from partially distinguishable and lossy GBS for both types of detectors. In the case of threshold detectors, the probability as calculated by the Torontonian is a special case under our framework. By analyzing the expressions of these probabilities we propose an efficient classical simulation algorithm which can be used to calculate the probabilities. Our model and algorithm provide foundations for an approximate method for calculating probabilities. It also allows for a way to design sampling algorithms that are not only compatible with existing algorithms for ideal GBS, but can also reduce their complexity exponentially, depending on the indistinguishability efficiency. Using this we show how the boundary of quantum supremacy in GBS can be affected by partial distinguishability.

Intellectual structure and pattern of publication in the International Journal of Innovation Science: a bibliometric study

PurposeThis study aims to sketch a bibliometric portrait of the International Journal of Innovation Science (IJIS) and attempts to evaluate its publication patterns from 2011 to 2020 by unfolding the key aspects of its publication trends for the audience of the journal and scholars of bibliometric studies as well.Design/methodology/approachThis study analyzes papers published in the IJIS from 2011 to 2020 by using the required bibliometric measures to analyze the key aspects of the publishing trends of IJIS.FindingsThis study finds that a total of 487 authors published 271 articles in IJIS during 2011–2020. The USA leads the table with 89 papers followed by India (29 papers) and China (26 papers). The degree of collaboration in IJIS ranged from 0.36 to 0.94. Moreover, this study finds that the keyword “design/methodology/approach” is the central theme of research in IJIS around which all other keywords revolve.Research limitations/implicationsThis study focuses on the publication patterns of the IJIS over a period of ten years. Patterns of research output in 271 publications are comprehended and analyzed. For making a ten-year bibliometric study, the papers published before 2011 were excluded from the purview of research.Practical implicationsReaders of the IJIS, teachers and research scholars interested in bibliometric studies can benefit from insights into the scholarly papers published in IJIS from 2011 to 2020.Originality/valueThis study would provide the readers of IJIS to ascertain significant contributions, top cited papers, the most prolific authors, geographical distribution of papers, keyword co-occurrence and bibliographic coupling.

Working characteristics of a magnetostrictive vibration energy harvester for rotating car wheels.

The practice of harvesting vibration energy from machine tools, windmill blades, etc., and converting it into electric energy to power low-power electronic circuits has attracted wide attention from experts and scholars. Abundant vibrations that exist in the moving vehicle can be harvested to power sensors in tire pressure monitoring. In this paper, for the first time, a device is proposed to harvest the rotational vibration energy with the iron-gallium alloy (magnetostrictive material) as the core material. Such a device utilizes the coupling characteristics of Villarreal effect and Faraday electromagnetic effect to convert the vibration energy generated by the moving vehicle into electric energy. Upon completion of the design of the magnetostrictive rotational vibration energy harvester, the influence law of key factors, including substrate material, substrate size, and pre-magnetization field arrangement on the harvesting capability of the device, was studied in detail through experiments. An electric motor and vibration exciter were used to apply varied excitation forms to the harvester, and the output patterns of the harvester under conditions of wheel rotation, road bumps, and random vibration were fully analyzed. In addition, the correlation between the deformation of the cantilever beam and harvester performance was also investigated. The results have shown that at the acceleration of 9.6 g and the rotational speed of 90 r/min, the harvester can reach the output voltage of 1.22 V. Consequently, it demonstrates the feasibility of employing the magnetostrictive harvester to gather rotational vibration energy and provides theoretical guidance for further and deeper research on the harvester.