Small Machine Research Articles

High Dimensional Quantum Machine Learning With Small Quantum Computers

Quantum computers hold great promise to enhance machine learning, but their current qubit counts restrict the realisation of this promise. To deal with this limitation the community has produced a set of techniques for evaluating large quantum circuits on smaller quantum devices. These techniques work by evaluating many smaller circuits on the smaller machine, that are then combined in a polynomial to replicate the output of the larger machine. This scheme requires more circuit evaluations than are practical for general circuits. However, we investigate the possibility that for certain applications many of these subcircuits are superfluous, and that a much smaller sum is sufficient to estimate the full circuit. We construct a machine learning model that may be capable of approximating the outputs of the larger circuit with much fewer circuit evaluations. We successfully apply our model to the task of digit recognition, using simulated quantum computers much smaller than the data dimension. The model is also applied to the task of approximating a random 10 qubit PQC with simulated access to a 5 qubit computer, even with only relatively modest number of circuits our model provides an accurate approximation of the 10 qubit PQCs output, superior to a neural network attempt. The developed method might be useful for implementing quantum models on larger data throughout the NISQ era.

Small-sample stacking model for qualitative analysis of aluminum alloys based on femtosecond laser-induced breakdown spectroscopy.

Material characterization using laser-induced breakdown spectroscopy (LIBS) often relies on extensive data for effective analysis. However, data acquisition can be challenging, and the high dimensionality of raw spectral data combined with a large-scale sample dataset can strain computational resources. In this study, we propose a small sample size stacking model based on femtosecond LIBS to achieve accurate qualitative analysis of aluminum alloys. The proposed three-layer stacking algorithm performs data reconstruction and feature extraction to enhance the analysis. In the first layer, random forest spectral feature selection and specific spectral line spreading are employed to reconstruct the data. The second layer utilizes three heterogeneous classifiers to extract features from the reconstructed spectra in different feature spaces, generating second-level reconstructed data. Finally, the third layer utilizes the reconstructed dataset for qualitative prediction. Results indicate that the Stacking algorithm outperforms traditional methods such as k-nearest neighbors (KNN), support vector machine (SVM), and random forest (RF), including those combined with principal component analysis (PCA). The Stacking algorithm achieves an impressive 100% recognition rate in classification, with Accuracy, precision, recall, and F1 scores reaching 1.0. Moreover, as the number of samples decreases, the gap between the recognition accuracy of the Stacking algorithm and traditional approaches widens. For instance, using only 15 spectra for training, the Stacking algorithm achieves a recognition accuracy of 96.47%, significantly surpassing the improved RF's accuracy of 71.76%. Notably, the model demonstrates strong robustness compared to traditional modeling approaches, and the qualitative prediction error remains consistently below 5%. These findings underscore the model's enhanced generalization ability and higher prediction accuracy in small sample machine learning. This research contributes significantly to improving the applicability of the LIBS technique for fast detection and analysis of small samples. It provides valuable insights into the development of effective methodologies for material characterization, paving the way for advancements in the field.

Development and Experimental Validation of an Agricultural Robotic Platform with High Traction and Low Compaction

Some researchers expect that future agriculture will be automated by swarms of small machines. However, small and light robots have some disadvantages. They have problems generating interaction forces high enough to modify the environment (lift a stone, cultivate the soil, or transport high loads). Additionally, they have limited range and terrain mobility. One option to change this paradigm is to use spikes instead of wheels, which enter the soil to create traction. This allows high interaction forces with the soil, and the process is not limited by the weight of the vehicle. We designed a prototype for mechanical soil cultivation and weeding in agricultural fields and evaluated its efficiency. A static and dynamic test was performed to compare the energy input of the electrical motor with precise measurements of the forces on the attached tool. The results indicate that the prototype can create interaction forces of up to 2082 N with a robot weight of 90 kg. A net traction ratio of 2.31 was reached. The dynamic performance experiment generated pull forces of up to 1335 N for a sustained net traction ratio of 1.48. The overall energy efficiency ratio for the machine reached values of up to 0.54 based on the created draft force and the measured input energy consumption.

New small-scale hydromechanical deep-drawing process using die-integrated active high-pressure generation system

In this study, hydraulic pressure generation and small-scale cylindrical hydromechanical deep-drawing experiments were conducted using a novel die-integrated active high-pressure generation system. The most significant feature is the installation of a hydraulic pressure-generating piston structure inside the die, which enables a high-pressure generation process of 100 MPa or higher inside the die. In addition, by taking advantage of the size effect of a smaller die, a high hydraulic pressure is actively generated using the same equipment as in conventional drawing processes. It was discovered that a piston installed in the die can actively generate a hydraulic pressure of 100 MPa or higher based on the Pascal principle. By downsizing the die, a hydraulic pressure of 100 MPa or higher can be generated using only the power of a small press machine (50 kN). By actively applying high hydraulic pressure counter and radial pressures, small-scale drawability can be significantly improved. Furthermore, the application of the proposed system to single-action presses and progressive dies can enable hydromechanical deep drawing with optimized conditions for each process in a single motion.

Exploring Washing Procedures for Produce Brush Washer

Previous environmental monitoring projects in food production facilities have revealed inconsistencies in how produce brush washer machines are cleaned after use; thus, the study of effective sanitation procedures for these machines is needed. Four chlorine solution treatments (ranging from 25 to 200 ppm), as well as a water-only treatment, were tested for efficacy in reducing bacterial loads for a selected small brush washer machine. Results indicate that rinsing with the machine’s power and water alone, a frequent practice among some produce processors, yielded a reduction of 0.91–1.96 log CFU per brush roller in bacterial counts, which was not statistically significant (p > 0.05). However, the chlorine treatments were found to be effective in reducing bacterial loads significantly, with higher concentrations being the most effective. The 200 ppm and 100 ppm chlorine treatments yielded bacterial reductions of 4.08 and 3.95 log CFU per brush roller, respectively, leaving bacterial levels statistically similar to the levels at postprocess decontamination, meaning these are the most effective at killing bacteria of all the chlorine concentrations tested. These data suggest the use of at least 100 ppm chlorine sanitizer solution is a good method to sanitize hard-to-clean produce washing machines, yielding an approximate 4 log CFU reduction of the inoculated bacteria.

Design of a prototype of a sweet mesquite pelletizing machine for feeding cattle and pigs

The present work consisted in designing a pelletizing machine for the production of animal feed from sweet mesquite. The designof the machine responded to the request of the clients, consisting of a small machine with a productivity of 640 kg day⁻¹in 8 hoursof work. During the machine design, the corresponding resistance calculations, sizing and selection of the appropriate materials forthe structure and other systems that make up the machine were made, such as: transmission system, transmission shaft, conditioningand pelletizing systems.The machine receives a pre-elaborated and crushed mixture, which is processed through the distribution, compression, cutting,unloading and packaging systems. The granulation system of the machine begins with the entry of food into the hopper, beingsubsequently distributed from the vanes towards the rollers in the compression system and traveling towards the face of a die. Therollers apply a compression force that forces the food to pass through the holes. Once the feed has been extruded, the pellets are cutby blades and stored at the bottom of the machine, where a container is placed. The average size of the pellet to be produced by theproposed design is: 10.55 mm in length with a diameter of 4.13 mm.

Critical Care Echocardiography

Ultrasonography is increasingly applied in the critical care setting. With advancements in technology, ultrasonography has become easier to use, with smaller machines, and more fundamental to patient assessment. Ultrasonography is a hands-on tool that brings real-time, dynamic information to the bedside. Patients in the critical care setting often have unstable hemodynamics or a tenuous respiratory status; thus, the use of ultrasonography to augment the assessment greatly improves patient safety. This article explores how to differentiate the etiology of shock with the adjunct of critical care echocardiography. In addition, the article examines how various ultrasonography techniques can be used to diagnose other life-threatening cardiac conditions, such as pulmonary embolism or cardiac tamponade, and the role of echocardiography in cardiopulmonary resuscitation. Critical care providers can add echocardiography and the information it provides to their repertoire to improve diagnosis, treatment, and patient outcomes.

Predicting potential areas at risk of the Dengue Hemorrhagic Fever in Jakarta, Indonesia—analyzing the accuracy of predictive hot spot analysis in the absence of small geographical area data

ABSTRACT Dengue Hemorrhagic Fever (DHF), a more severe form of dengue, is one of the most rapidly spreading mosquito-borne diseases in the world. This study is motivated by the rising DHF incidence in Jakarta, the capital city of Indonesia. We mainly utilized hot spot analysis, which employs spatial statistics to find at-risk areas for DHF outbreaks in Jakarta’s five municipalities. However, producing informative results from hot spot analysis requires a complete set of data on each of Jakarta’s 42 districts, which is not available. We thus propose the idea of using small area estimation (SAE) and machine learning to make up for the lack of data. To evaluate whether this proposed method is effective, we compare the hot spot results from the estimation with the actual data of each district. The results show that the estimated hot spot map is similar to the hot spot map from the actual data. This implies that it is possible to find potential at-risk areas of dengue fever without a complete dataset in every small geographic area. We expect that this research can increase the performance of DHF control measures at the district level, even in the absence of small area data.

Modelling and Analysis of Inter-Turn Short-Circuit Fault of PM Machines With Parallel-Connected Coils

This paper presents a general analytical fault model in a compact matrix form for surface-mounted permanent magnet (SPM) machines with parallel-connected coils, which is useful to study the machine performance under the inter-turn short circuit (ITSC) fault. To simplify the fault model, the multiphase Clarke transformation has been proposed. In the model, the branch currents rather than the phase currents are employed as state variables to describe machine behaviours under fault. Additionally, self- and mutual-inductances are obtained by winding function approach (WFA) plus slot permeance method. The proposed analytical fault model is applied to a 3 kW 96-slot 32-pole SPM machine and validated by time-stepping FE simulations. A small scale 12-slot 4-pole SPM machine prototype has also been built to further validate the accuracy of the proposed fault model.

Sensitized piRNA reporter identifies multiple RNA processing factors involved in piRNA-mediated gene silencing.

Metazoans guard their germlines against transposons and other foreign transcripts with PIWI-interacting RNAs (piRNAs). Due to the robust heritability of the silencing initiated by piRNAs in Caenorhabditis elegans (C. elegans), previous screens using C. elegans were strongly biased to uncover members of this pathway in the maintenance process but not in the initiation process. To identify novel piRNA pathway members, we have utilized a sensitized reporter strain which detects defects in initiation, amplification, or regulation of piRNA silencing. Using our reporter, we have identified Integrator complex subunits, nuclear pore components, protein import components, and pre-mRNA splicing factors as essential for piRNA-mediated gene silencing. We found the small nuclear processing cellular machine termed the Integrator complex is required for both type I and type II piRNA production. Notably, we identified a role for nuclear pore and nucleolar components NPP-1/Nup54, NPP-6/Nup160, NPP-7/Nup153, and FIB-1 in promoting the perinuclear localization of anti-silencing CSR-1 Argonaute, as well as a role for Importin factor IMA-3 in nuclear localization of silencing Argonaute HRDE-1. Together, we have shown that piRNA silencing in C. elegans is dependent on evolutionarily ancient RNA processing machinery that has been co-opted to function in the piRNA-mediated genome surveillance pathway.

3D printed guide tube system for acute Neuropixels probe recordings in non-human primates

Objective. Neuropixels (NP) probes are a significant advance in electrophysiological recording technology that enable monitoring of hundreds of neurons in the brain simultaneously at different depths. Application of this technology has been predominately in rodents, however widespread use in non-human primates (NHPs) such as rhesus macaques has been limited. In this study we sought to overcome two overarching challenges that impede acute NP implantation in NHPs: (1) traditional microdrive systems that mount to cephalic chambers are commonly used to access cortical areas for microelectrode recordings but are not designed to accommodate NP probes, and (2) NHPs have thick dura mater and tissue growth within the cephalic chambers which poses a challenge for insertion of the extremely fragile NP probe. Approach. In this study we present a novel NP guide tube system that can be adapted to commercial microdrive systems and demonstrate an implant method using the NP guide tube system. This system was developed using a combination of CAD design, 3D printing, and small part machining. Software programs, 3D Slicer and SolidWorks were used to target cortical areas, approximate recording depths and locations, and for in-silico implant testing. Main results. We performed in vivo testing to validate our methodology, successfully implanting, explanting, and reimplanting NP probes. We collected stable neurophysiological recordings in the premotor cortex of a rhesus macaque at rest and during performance of a reaching task. Significance. In this study we demonstrate a robust Neuropixels implant system that allows multiple penetrations with the same NP probe and share design files that will facilitate the adoption of this powerful recording technology for NHP studies.

Design and Fabrication of Solar Seed Sowing Machine Using Remote Control

The aim of this project is to develop a lightweight, economical and reliable seed sowing machine that will increase the efficiency of the crop produced and also to develop a better mechanical machine to help the agriculture field which reduce the amount and type of work spend on one crop. Hence in this work of project we decided to design and build a machine which will be available for farmer of small scale production at cheaper rate also which can reduce their expenditure and the profit of farmer at the same time. The main specialty of this projects that it can also sow cotton seed with ease. The agriculture field needs to find solutions on old agricultural technique and replace them with more efficient technique. In this project we tried to design and fabricate machine to reduce target energy input in more efficient way than in the past. The advent of autonomous system architecture gives us opportunity to develop a new range of agricultural equipment based on small smart machine that can do the right thing in the right place at the right time in the right way. It will increase productivity and decrease expenses in agriculture sector. In agriculture, the opportunities for robot can increase efficiency and the robots are on farms in various appearances and with new technologies are in increasing numbers. The proposed robot design can perform the agricultural operations such as seed sowing and it is a remote controlled robot with reciprocating action of a seeding mechanism. Keywords: Agriculture, remote control, solar panel, seed (groundnut.

Home dialysis therapies

Home dialysis therapies offer a significant benefit to patients in respect of quality of life and autonomy, as compared with in-centre haemodialysis. There is significant unwarranted variation across the world in the availability of both peritoneal dialysis (PD) and home haemodialysis, which has led in the UK to a recommendation of a minimum 20% prevalent rate of dialysis patients at home. Key advances in PD have included changes in the approach to prescribing PD and the use of assisted dialysis. Peritonitis remains a significant complication which may present to general physicians and needs prompt recognition and treatment. The development of novel small dialysis machines has led to a resurgence of interest in home haemodialysis.

Deletion of the stress response protein REDD1 prevents impaired cardiac function in diabetic mice

The overwhelming impact of heart failure on morbidity and mortality in obesity and type 2 diabetes requires a deeper understanding of the molecular events that mediate cardiac dysfunction. We recently demonstrated using in vivo and in vitro models of diabetes that upregulation of endoplasmic reticulum stress in cardiomyocytes promoted expression of the stress response protein regulated in development and DNA damage 1 (REDD1). REDD1 has been implicated in diabetes-induced functional deficits in both the retina and kidney; however, a role for REDD1 in diabetes-induced cardiac dysfunction has not been investigated. Thus, we explored the hypothesis that REDD1 contributes to the development of diabetes-induced cardiac dysfunction. To induce diabetes, 6-week old male wild-type and REDD1 knock-out (KO) B6;129 mice were fed a high-fat high-sugar diet (42% kcal fat, 34% sucrose by weight) for 16 weeks; 2 weeks after initiation of the diet, mice were administered low-dose streptozotocin (STZ) for five consecutive days. Non-diabetic control mice were fed a standard rodent diet and received vehicle injections. Mice with a fasting blood glucose level >250mg/dL were defined as diabetic. At 10 weeks of age, transthoracic echocardiogram was evaluated every 2 weeks using a GE Logique small animal echocardiography machine. After 12 weeks of diabetes, left ventricular ejection fraction (EF) was reduced in diabetic wild-type mice as compared to non-diabetic wild-type mice (51.0 +/-9.8% versus 39.5 +/- 5.5%, p = 0.015). Meanwhile, EF in diabetic REDD1 KO mice (47.4 +/- 6.6%) was similar to that observed in non-diabetic REDD1 KO mice (49.6 +/- 6.7%). To investigate a potential cause of the preserved EF in diabetic REDD1 KO mice, tissue homogenates from the left ventricle were examined by PCR analysis. REDD1 mRNA expression in diabetic wild-type mice was enhanced as compared to non-diabetic controls in coordination with increased expression of Tgfb1, as well as expression of the pro-fibrotic genes Fn1, Col1a1, and Col3a1. By contrast, there was no increase in pro-fibrotic mRNA expression in cardiac tissue homogenates from diabetic REDD1 KO mice, as compared to non-diabetic REDD1 KO mice. Overall, the data support a role for REDD1 expression in the development of impaired cardiac function and the pro-fibrotic response of the heart to diabetes. This is the full abstract presented at the American Physiology Summit 2023 meeting and is only available in HTML format. There are no additional versions or additional content available for this abstract. Physiology was not involved in the peer review process.

Bootstrap Embedding on a Quantum Computer

We extend molecular bootstrap embedding to make it appropriate for implementation on a quantum computer. This enables solution of the electronic structure problem of a large molecule as an optimization problem for a composite Lagrangian governing fragments of the total system, in such a way that fragment solutions can harness the capabilities of quantum computers. By employing state-of-art quantum subroutines including the quantum SWAP test and quantum amplitude amplification, we show how a quadratic speedup can be obtained over the classical algorithm, in principle. Utilization of quantum computation also allows the algorithm to match─at little additional computational cost─full density matrices at fragment boundaries, instead of being limited to 1-RDMs. Current quantum computers are small, but quantum bootstrap embedding provides a potentially generalizable strategy for harnessing such small machines through quantum fragment matching.

Modeling the interaction between a new four-bar subsoiling mechanism and red soil using the improved differential evolution algorithm and DEM

Because of the poor subsoiling effects and high tillage resistances of small subsoiling machines when used on red soil in southern China, a new subsoiling mechanism based on functional bionics and an optimization method that employed an improved differential evolution (IDE) algorithm are proposed in this paper. The tillage performance was improved by causing the subsoiler to mimic the digging motion of a mole forefoot. The path synthesis of the subsoiling mechanism was solved by the IDE, and the tillage performance of the four-bar bionic subsoiling mechanism was evaluated by the discrete element method. First, the digging trajectory of the mole forefoot was mapped as the desired subsoiling trajectory. An optimization model for the path synthesis was established to minimize the position error between the desired subsoiling trajectory and the coupler curve of the mechanism; it was solved by the differential evolution algorithm with improvements in the mutation and crossover operations. It was found that the IDE could more rapidly search for a more accurate solution. The optimization results were used to design a bionic subsoiling mechanism that could mimic the digging trajectory of a mole forefoot. Second, the microscopic contact parameters among the soil particles were calibrated by soil accumulation and direct shear tests. In addition, a discrete element soil model was established that included dual coupling of variable contact models for the tillage layer and the plow pan. The tillage processes of an existing common subsoiling mechanism (CSM), the bionic subsoiling mechanism equipped with a common subsoiler (BSM&CS), and the bionic subsoiling mechanism equipped with a bionic subsoiler (BSM&BS) were analyzed by a joint ADAMS and EDEM simulation. The simulation results were analyzed according to established evaluation indexes for tillage performance. The comprehensive soil disturbance performance of the BSM&CS improved by 257.03% and its drag reduced by 10.87% from the CSM values, while the comprehensive soil disturbance performance of the BSM&BS improved by 312.78% and its drag reduced by 18.40% from the CSM values. Finally, the driving parameter combination for the BSM was optimized using the central composite design method.

Research on the evaluation method of agricultural intelligent robot design solutions.

At present, agricultural robots are produced in large quantities and used in agricultural planting, and the traditional agricultural model is gradually shifting to rely on the Internet of Things and sensors to accurately detect crop growth information. The scientific and rational design of agricultural robots plays a huge role in planting and production efficiency, however, the factors affecting their design are complex and ambiguous, so it is necessary to use a rational evaluation system to make a preferential decision among multiple design options. In order to reduce the subjectivity and blindness of program selection in the process of agricultural robot design, make the decision more objective and reasonable, and thus enhance the practicality and scientificity of the program, a new comprehensive evaluation method based on user requirements is proposed. First, after researching and interviewing users and farming operations, obtaining raw information on requirements, using the Kano model to classify the requirements and establishing an evaluation index system. Secondly, the combination of hierarchical analysis(AHP) and entropy weighting method is used to assign weights to the evaluation index system, calculate the weight value and importance ranking of each index, and carry out various program designs based on the ranking. Finally, the VIKOR method was applied to evaluate and rank the design solutions. The new evaluation method can better complete the preferential decision of the agricultural robot design scheme and get a more perfect design scheme, which reduces the influence of human subjective thinking in the decision-making process. The method not only corrects the traditional evaluation method, but also effectively improves the accuracy and comprehensiveness of the design evaluation process. It also provides a reference for designers to preferably select design solutions and promotes the development of small mobile machines in the context of smart agriculture.

High-fidelity modeling of dynamic origami folding using Absolute Nodal Coordinate Formulation (ANCF)

Origami has evolved into a framework for creating engineering systems at vastly different scales: from large deployable airframes to architected materials to small DNA machines. These emerging applications require us to develop high-fidelity models that can simulate and examine folding-induced mechanical responses, especially those involving significant facet rotation, non-uniform deformation, and complex dynamics. To this end, this study formulates and experimentally validates a new origami mechanics model based on Absolute Nodal Coordinate Formulation (ANCF), which has unique advantages for predicting the nonlinear dynamics of multibody systems with large rotation and deformation. This new model treats origami facets as ANCF thin plate elements rotating around compliant creases. Moreover, Torsional Spring Damper Actuator (TSDA) connectors are developed to represent crease folding. After careful calibration with experimentally measured constitutive material properties, this study provides the first reported quantitative agreement between simulation predictions and experiment results involving complex and non-uniform facet deformation and transient dynamic responses. Therefore, this model can help deepen our knowledge of folding-induced mechanics and dynamics, fostering future applications for origami.

The Design of a New Type Fruit Dicing Machine

The demand for fruit is very large, especially fresh-cut fruit is more and more popular, custom-cut fruit machine has emerged. However, the current market of automatic cutting machine exists in general low efficiency, poor applicability of the problem. The author has carried on the market research according to the people's consumption habit, and has completed a new-type fruit cutting machine design. In this paper, a small automatic dicing machine is designed for household use, which adopts the design idea of household appliances, in the work efficiency, product appearance, the use of experience and manufacturing costs to give the most appropriate solution, the use of rotary cutter plus combination of cutter design of raw materials to cut into ding. The structure of the cutting machine is designed by 3D modeling software, and the rationality of the design is verified by movement simulation and finite element analysis. After the design is completed, some physical models are made to verify the working principle of the core structure, and the improvement scheme is put forward. The experiment shows that the fruit cutting machine can complete the specified task, cutting efficiency is higher, fruit waste less, fill the gap in the market, but also provide a reference for other designers.

African traditional foods and sustainable food security

Dietary diversity is key to sustainable food security and part of Africa's rich biodiversity heritage are hundreds of lesser-known indigenous crops and wild food plants that are important components of African traditional diets. African traditional foods and African food processing techniques are part of the rich cultural heritage of the people. Fermentation and sun-drying are two of the most important African traditional food processing techniques used for the production of a wide range of processed food products and for low-cost food preservation under non-refrigeration conditions. Lactic acid fermentation is used for the production of a variety of African traditional foods from plant and animal sources that are safe, nutritious and contribute to food security. Some of the organisms are probiotics that offer distinct health benefits. However, African traditional foods are still largely prepared in the home and the unregulated informal food sector. Their production is characterized by slow, manual operations; the processes are not standardized and the quality of the products are variable and often poor. There are serious safety concerns with many African traditional foods and beverages largely on account of the unhygienic conditions under which they are prepared, the quality of the raw materials and the packaging. Another safety concern with regards to African traditional fermented foods is foodborne antimicrobial resistance (AMR) in bacteria that reduces the options for treating human and animal diseases. Some successes have been recorded in reducing the drudgery associated with African traditional food processing, carried out mainly by women, and increasing the capacity, efficiency and safety of the processes and the quality of the products through the introduction of small machines for small-scale industrial production. Solar drying eliminates the problem of poor quality and unsafe products associated with the traditional open air, shallow layer sun-drying. Even though considerable amount of research has been carried out on upgrading African traditional foods, they remain largely at the bench stage. The establishment of zonal or regional food pilot plants will facilitate the commercialization of research findings from African universities and research institutes, improve traditional foods and processes, and promote sustainable food security.