Small Box Research Articles

On the two-dimensional harmonic oscillator with an electric field confined to a circular box

Abstract We revisit the quantum-mechanical two-dimensional harmonic oscillator with an electric field confined to a circular box of impenetrable walls. In order to obtain the energy spectrum we resort to the Rayleigh-Ritz method with polynomial and Gaussian basis sets. We compare present results with those derived recently by other authors. We discuss the limits of large and small box radius and also do some calculations with perturbation theory.

A data density-based measure of dexterity for continuum robots and its comparative study

Abstract Continuum robot-based surgical systems are becoming an effective tool for minimally invasive surgery. A flexible, dexterous, and compact robot structure is suitable for carrying out complex surgical operations. In this paper, we propose performance metrics for dexterity based on data density. Data density at a point in the workspace is higher if the number of reachable points is higher, with a unique configuration lying in a small square box around a point. The computation of these metrics is performed with forward kinematics using the Monte Carlo method and, hence, is computationally efficient. The data density at a particular point is a measure of dexterity at that point. In contrast, the dexterity distribution property index is a measure of how well dexterity is distributed across the workspace according to desired criteria. We compare the dexterity distribution property index across the workspace with the dexterity index based on the dexterous solid angle and manipulability-based approach. A comparative study reveals that the proposed method is simple and straightforward because it uses only the position of the reachable point as the input parameter. The method can quantify and compare the performance of different geometric designs of hyper-redundant and multisegment continuum robots based on dexterity.

Research on flexural behavior and design method of formwork free UHPC wet joint in prefabricated small box girder bridges

This study aims to enhance the bearing capacity of wet joints in prefabricated small box girder bridges while simplifying the on-site construction process. Experimental tests were conducted on formwork-free ultra-high-performance concrete (UHPC) wet joints, focusing on failure modes, ultimate flexural capacities, and cracking and strain behaviors. These were compared to the behaviors observed in rectangular and funnel-shaped wet joints. The results demonstrate that the width of the joint significantly influences flexural performance, with the horizontal strip playing a crucial role in resisting cracks. It is recommended that for formwork-free UHPC wet joints, the strip height h2 should be no less than 0.1 times the thickness of the bridge deck, and the joint width W should be at least eight times the diameter of the transverse steel reinforcement. Considering the contribution of UHPC in the tensile zone, formulas were developed to calculate the flexural capacity of UHPC-normal concrete (NC) composite section beams. Based on these flexural test results and numerical analysis, a design method for formwork-free UHPC wet joints is proposed.

A combined experimental-mathematical study on the kinetics of dry ice sublimation under different airflow velocities and blowing modes

The sublimation rate of dry ice, crucial for its cooling performance, is typically influenced by environmental temperature, pressure, and specific surface area. However, the effect of wind speed under forced air convection is not well understood, and current sublimation kinetic models inadequately capture this influence, leading to discrepancies between simulations and experiments. This study examines the sublimation kinetics of static dry ice particles under varying wind speeds and blowing modes. A mathematical model was developed to determine the sublimation kinetic parameters by integrating the Clausius-Clapeyron equation, mass transfer theory, and hybrid particle swarm optimization (HPSO) algorithm. These parameters were then used to create a cooling model for a small insulated box, and the results were validated against experimental data. The findings show that increasing wind speed enhances the sublimation rate of dry ice, with upward-blowing conditions resulting in higher rates than side-blowing conditions. The model’s predictions closely match experimental data, with a maximum mass change deviation of less than 3 % and a maximum temperature deviation of less than 4 °C, demonstrating high reliability.

On the Cosmic Variance of the Merger Rate Density of Binary Neutron Stars

The cosmic variance on the star formation history may lead to bias in the merger rate density estimation of binary neutron star (BNS) mergers by compact binary population synthesis. In this paper, we take advantage of the large box size of the Millennium Simulation combined with the semianalytic galaxy formation model GABE and the parameterized population binary star evolution model to examine how much effect the cosmic variance will introduce on the estimation of the merger rate density of BNS mergers. We find that for subbox sizes of 100 and 200 Mpc, the variance of merger rate density σ R /R at different redshifts is about 23%–35% and 13%–20%, respectively. On the one hand, as for the variance of the detection rate on BNS mergers with the current LIGO–Virgo–KAGRA (LVK) detector network, this value is very small at ≲10%, which indicates ignoring the cosmic variance is reasonable for estimating the merger rate density from current LVK observations. On the other hand, with next-generation gravitational wave detectors, it is possible to localize BNS mergers within subboxes possessing a length of 40 Mpc for a source redshift z s < 0.2. In such a small box, the cosmic variance of the merger rate density is significant, i.e., the value of σ R /R is about ∼55%. This hints that estimating the merger rate density of BNS in different sky areas may provide useful information on the cosmic variance.

A lightweight joint metric detection approach on YOLO for hot spots in photovoltaic modules

The hot spot effect is one of the primary causes of damage to photovoltaic (PV) modules and a significant factor contributing to the decline in their power generation capacity. Thermal imaging inspection of PV modules is an indispensable aspect of PV plant operation and maintenance. This article introduces a lightweight detection algorithm for hot spots in PV modules based on an enhanced version of YOLOv8. The algorithm incorporates a lightweight convolution operator, Volumetric Grid Spatial Cross Stage Partial, as a replacement for the original C2f operator, resulting in effective reduction of the model's parameter size and improved detection speed. Additionally, the Content-Aware ReAssembly of FEatures upsampling operator is utilized instead of the nearest-neighbor algorithm during the upsampling process, thereby minimizing the loss of hot spot feature information. Furthermore, a joint metric approach combining the Complete Intersection over Union metric and the normalized Wasserstein distance metric is proposed to calculate the localization loss of the target bounding boxes, thereby enhancing the regression accuracy of small hot spot prediction boxes. Experimental results demonstrate that the improved YOLOv8 network enables fast and accurate detection of hot spots. This method achieves an impressive average precision of 98.8% and a high detection speed of 218.3 fps.

Study on the Design Method of Small Black Box for Aircraft that Satisfies Extreme Environment Requirements

Study on the Design Method of Small Black Box for Aircraft that Satisfies Extreme Environment Requirements

Local mean value estimates for Weyl sums

We obtain new estimates –both upper and lower bounds– on the mean values of the Weyl sums over a small box inside of the unit torus. In particular, we refine recent conjectures of C. Demeter and B. Langowski (2022), and improve some of their results.

Local Symmetry Deviation from the Average Structure of MnAs Revealed by Pair Distribution Function.

MnAs is an interesting material due to its magnetocaloric properties, which can be utilized in magnetic refrigeration. However, despite major efforts, its magnetic refrigeration performances in the substituted forms could not be improved compared to the parent MnAs phase. Both small and big box modeling of the pair distribution function of MnAs for the local structure description and powder X-ray diffraction for the average structure reveal an inherent local orthorhombic distortion in the hexagonal structure of MnAs. As a result of this distortion, any modification to the hexagonal structure results in an orthorhombic structure and a weaker magnetocaloric performance. This study highlights the importance of studying local distortion in magnetic materials. This is achieved by combining X-ray absorption spectroscopy with total scattering X-ray diffraction.

Safety Evaluation for Fabricated Small Box Girder Bridges Based on Fuzzy Analytic Hierarchy Process and Monitoring Data.

During the operation of fabricated small box girder bridges, which face safety issues such as structural degradation and failure, there is an urgent need to propose a safety evaluation method to cope with the possible risks. This article quantitatively evaluates the safety state of a fabricated small box girder bridge in Wuhan City based on Fuzzy Analytic Hierarchy Process (FAHP) and structural health monitoring (SHM) data. Firstly, the FAHP model is established, and stress, deformation, and temperature are selected as evaluation factors. The safety thresholds of stress and deformation are determined by combining the industry specifications and the historical statistical patterns of the massive SHM data. The temperature field of the bridge is simulated and analyzed by combining ANSYS, HYPERMESH, and TAITHREM, and the most unfavorable temperature gradient is determined as a threshold for the safety evaluation. Finally, the scores of indexes of the bridge are determined based on the measured SHM data, which in turn provides a quantitative description of the safety state. The results show that the thresholds determined by the joint industry specifications and the massive SHM data are reasonable; the temperature field simulation model established in this article is consistent with the measured results, and can accurately determine the temperature gradient of the bridge. The safety evaluation result from the FAHP model is the same as the field test results, which verifies the effectiveness and applicability of the proposed method to actual bridge projects.

PENGGUNAAN ALGORITMA GEOSHASHING DALAM PENCARIAN LETAK INFORMASI GEOGRAFIS PENGGANTI KOOORDINAT LATITUDE DAN LONGITUDE

In the digital age when the search for geographic data is becoming increasingly important in location applications, including mapping, navigation, and analysis of the environment of a place within a location. Geohashing algorithms offer an efficient approach to encoding and storing geographic data in string format, these strings use alphanumeric generated by geohashing of numbers and letters in the search for location points by coordinates, it can also offer an access layer of sensitive location data. This study aims to explore the application of geohashing algorithms in geographic data management. Geohashing algorithm in the search for the location of geographic information as an alternative to latitude and longitude coordinates. In particular, this study analyzes the efficiency of geohashing in data compression, the localization accuracy of geohashing use allows for better grouping of geographic data, and supports spatial data search such as location search and coordinate point search within a specific region. Geohashing algorithms are implemented in geographic data and tested for various search scenarios. From the results of the study showing that geohashing can significantly increase the speed of searching for geographic information, the geohashing algorithm proves its action as an effective tool in the management and search of geographic data, in the search for location coordinate data, it can also provide an alternative to get the latitude and longitude of a location. The results show that geohashing can significantly increase the speed of searching for geographic information, especially in reaching a location with a small and large data box grid level according to the entered string characters. The use of geohashing not only improves the efficiency and speed of searches but also provides additional benefits in terms of the management and protection of geographic data. Testing on this system is carried out by providing geographic access to the location application API that has been created on demand to obtain geographic data information and location points.

The Role of Cacao and Chocolate in Transpacific Exchange Part II. Cacao as Transpacific Trade Good and Global Commodity

In the course of the second half of the sixteenth century, chocolate and cacao became increasingly popular among many Europeans. By the 1630s if not earlier, not only the Spanish but also the Dutch, the French, and even the English were consuming a fair amount of cacao. Cacao drinking was introduced into Britain in 1657, and by the early eighteenth century ‘chocolaterías’ existed throughout London, competing with the traditional coffee houses. The drinking of cacao received the support of Quakers, who considered chocolate to be a welcome substitute for ginger. Chocolate was frequently sent as a present from New Spain, both to Spaniards living in Asia and to residents in Spain: In 1621, the Count of Santiago sent some small boxes of chocolate to his wife; in 1625, the Countess of Santiago of New Spain sent, among other things, boxes of chocolate and cacao to the Marchioness of Belvedere in Madrid.

Design and experiment of high-performance small magnetic shielding box

Investigating the state of cells in zero magnetic or near-zero magnetic environments is an important scientific issue. However, standard cell culture incubators can only provide general conditions such as constant temperature, constant humidity, sterility, and carbon dioxide, and cannot provide zero magnetic or near-zero magnetic environments for cell culture. To address this issue, an optimization method was proposed in this paper based on the combination of the particle swarm optimization algorithm (PSO) and the finite element method (FEM), achieving the optimization design of a magnetic shielding box (MSB) with a small volume, high shielding factor, and low residual field. Firstly, the high-permeability layer and high-conductivity layer were optimized respectively using the PSO and FEM. Then, the effectiveness of this method was analyzed through experiments. The experimental results show that the shielding factors in three directions at the center point of the optimized MSB are 786.8 (east-west), 2182.7 (north-south), and 1389.4 (vertical) respectively at 0.01 Hz. Meanwhile, the maximum residual field in the cubic region with a side length of 10 cm inside the MSB is 11.9 nT. Finally, the MSB designed by this method was placed in a standard cell culture incubator to cultivate cells in a zero-magnetic or near-zero magnetic environment. Then the Cell Counting Kit-8 (CCK8) experiments to evaluate the cytotoxicity of chemotherapy drugs on tumor cells in a weak magnetic environment (WMF). The results show that the lethality of paclitaxel (PTX) to Epidermal carcinoma cell (A431) increases by 25.96 times and the lethality of gemcitabine (GE) to Lung carcinoma cell (NCI-H460) increases by 24.23 times in a WMF. At the same time, the maximum proliferation inhibition rate of 5-fluorouracil (5-FU) on NCI-H460 cells in a WMF environment increased by 15.69%. That is, WMF could significantly improve the therapeutic effect of chemotherapy drugs on tumor cells.

Enhancing Medical Imaging Segmentation with GB-SAM: A Novel Approach to Tissue Segmentation Using Granular Box Prompts.

Recent advances in foundation models have revolutionized model development in digital pathology, reducing dependence on extensive manual annotations required by traditional methods. The ability of foundation models to generalize well with few-shot learning addresses critical barriers in adapting models to diverse medical imaging tasks. This work presents the Granular Box Prompt Segment Anything Model (GB-SAM), an improved version of the Segment Anything Model (SAM) fine-tuned using granular box prompts with limited training data. The GB-SAM aims to reduce the dependency on expert pathologist annotators by enhancing the efficiency of the automated annotation process. Granular box prompts are small box regions derived from ground truth masks, conceived to replace the conventional approach of using a single large box covering the entire H&E-stained image patch. This method allows a localized and detailed analysis of gland morphology, enhancing the segmentation accuracy of individual glands and reducing the ambiguity that larger boxes might introduce in morphologically complex regions. We compared the performance of our GB-SAM model against U-Net trained on different sizes of the CRAG dataset. We evaluated the models across histopathological datasets, including CRAG, GlaS, and Camelyon16. GB-SAM consistently outperformed U-Net, with reduced training data, showing less segmentation performance degradation. Specifically, on the CRAG dataset, GB-SAM achieved a Dice coefficient of 0.885 compared to U-Net's 0.857 when trained on 25% of the data. Additionally, GB-SAM demonstrated segmentation stability on the CRAG testing dataset and superior generalization across unseen datasets, including challenging lymph node segmentation in Camelyon16, which achieved a Dice coefficient of 0.740 versus U-Net's 0.491. Furthermore, compared to SAM-Path and Med-SAM, GB-SAM showed competitive performance. GB-SAM achieved a Dice score of 0.900 on the CRAG dataset, while SAM-Path achieved 0.884. On the GlaS dataset, Med-SAM reported a Dice score of 0.956, whereas GB-SAM achieved 0.885 with significantly less training data. These results highlight GB-SAM's advanced segmentation capabilities and reduced dependency on large datasets, indicating its potential for practical deployment in digital pathology, particularly in settings with limited annotated datasets.

Design and Implementation of a Low-Power Device for Non-Invasive Blood Glucose

Glucose is a simple sugar molecule. The chemical formula of this sugar molecule is C6H12O6. This means that the glucose molecule contains six carbon atoms (C), twelve hydrogen atoms (H), and six oxygen atoms (O). In human blood, the molecule glucose circulates as blood sugar. Normally, after eating or drinking, our bodies break down the sugars in food and use them to obtain energy for our cells. To execute this process, our pancreas produces insulin. Insulin “pulls” sugar from the blood and puts it into the cells for use. If someone has diabetes, their pancreas cannot produce enough insulin. As a result, the level of glucose in their blood rises. This can lead to many potential complications, including blindness, disease, nerve damage, amputation, stroke, heart attack, damage to blood vessels, etc. In this study, a non-invasive and therefore easily usable method for monitoring blood glucose was developed. With the experiment carried out, it was possible to measure glucose levels continuously, thus eliminating the disadvantages of invasive systems. Near-IR sensors (optical sensors) were used to estimate the concentration of glucose in blood; these sensors have a wavelength of 940 nm. The sensor was placed on a small black parallelepiped-shaped box on the tip of the finger and the output of the optical sensor was then connected to a microcontroller at the analogue input. Another sensor used, but only to provide more medical information, was the heartbeat sensor, inserted into an armband (along with the microprocessor). After processing and linear regression analysis, the glucose level was predicted, and data were sent via the Bluetooth network to a developed APP. The results of the implemented device were compared with available invasive methods (commercial products). The hardware consisted of a microcontroller, a near-IR optical sensor, a heartbeat sensor, and a Bluetooth module. Another objective of this experiment using low-cost and low-power hardware was to not carry out complex processing of data from the sensors. Our practical laboratory experiment resulted in an error of 2.86 per cent when compared to a commercial product, with a hardware cost of EUR 8 and a consumption of 50 mA.

Recognition and analysis system of steel stamping character based on machine vision

During the packaging process, it is essential to detect the steel stamping characters inside the box to identify any missing or repeated characters. Currently, manual detection suffers from low efficiency and a high false detection rate. To address these challenges, a steel stamping character recognition and analysis system based on machine vision has been developed. The enhanced YOLOv7 detection method was employed for character identification, complemented by a statistical analysis approach to achieve automated judgment and detection. To address the issue of size disparity between large and small characters, a small size anchor box and a larger detection head were integrated. Furthermore, modifications were made to the output structure of the YOLOv7 prediction network to enhance multi-scale detection capabilities. The inclusion of the location attention convolution module bolstered global feature extraction, thereby enhancing the detection accuracy of similar characters. Moreover, the utilization of a hash table was used to improve the efficiency of mapping steel stamping character recognition sequences. The experimental results demonstrate that the enhanced model achieves an accuracy of 99.83%, with a processing efficiency of 10.5 ms per single frame. These findings align with the performance criteria for automatic recognition and analysis of steel stamping characters.

Quantifying Visual Differences in Drought-Stressed Maize through Reflectance and Data-Driven Analysis

Environmental factors, such as drought stress, significantly impact maize growth and productivity worldwide. To improve yield and quality, effective strategies for early detection and mitigation of drought stress in maize are essential. This paper presents a detailed analysis of three imaging trials conducted to detect drought stress in maize plants using an existing, custom-developed, low-cost, high-throughput phenotyping platform. A pipeline is proposed for early detection of water stress in maize plants using a Vision Transformer classifier and analysis of distributions of near-infrared (NIR) reflectance from the plants. A classification accuracy of 85% was achieved in one of our trials, using hold-out trials for testing. Suitable regions on the plant that are more sensitive to drought stress were explored, and it was shown that the region surrounding the youngest expanding leaf (YEL) and the stem can be used as a more consistent alternative to analysis involving just the YEL. Experiments in search of an ideal window size showed that small bounding boxes surrounding the YEL and the stem area of the plant perform better in separating drought-stressed and well-watered plants than larger window sizes enclosing most of the plant. The results presented in this work show good separation between well-watered and drought-stressed categories for two out of the three imaging trials, both in terms of classification accuracy from data-driven features as well as through analysis of histograms of NIR reflectance.

Effect of spontaneous micro-fermentation on the physicochemical characteristics of Theobroma cacao L. beans

Objective: To evaluate the physicochemical characteristics of cacao beans during the spontaneous fermentation process in tepemixtle wooden boxes of three different sizes. Design/Methodology/Approach: Trinitarian-type cacao (Theobroma cacao L.) fruits were collected in a commercial orchard. The beans were fermented in boxes with the following operating conditions: volume of cacao with pulp, box size, a six-day period, and uncontrolled temperature and pH. The experiments were carried out in triplicate and an analysis of variance and a multiple comparison of means were performed with the Tukey test (p&lt;0.05) using the R program. Results: The parameters evaluated had the same behavior in the 4 kg box than in the 25 kg box and the 60 kg box, which indicates that the physicochemical and quality characteristics of cacao beans are not impacted by the decrease in the box size. Therefore, smaller boxes are viable for small-scale fermentations. Study Limitations/Implications: Only cacao beans from the Trinitarian genetic group were evaluated. Findings/Conclusions: Small-scale fermentations can be an option for the evaluation of varieties when the beans must be fermented for the sensory analysis of their qualitative attributes. This micro-fermentation methodology can also be incorporated into genetic improvement programs or the evaluation of the processes aimed at their optimization.

Damage analyze of prestressed small box girder bridges under explosive loading of vehicle

Damage analyze of prestressed small box girder bridges under explosive loading of vehicle

The die for the production of the hammered kaptorgas from Kouřim, Central Bohemia

Kaptorgas were small trapezoidal boxes with lids worn by women and girls in early medieval central Europe as magic or protective amulets. The paper presents a new find of a bronze cast die for hammering the front side of kaptorgas, which was excavated at the Nad Dolnicí settlement site located in the hinterland of the important central Bohemian hillfort of Kouřim. The die was used to produce type 1A kaptorgas with a motif of a four-legged eared gryphon with an indication of a wing and a tail ending in a floral decorative element. Although kaptorgas with this particular motif have not been recorded in Bohemia, it has analogies in Bulgaria and Poland. Based on the stylistic assessment of this originally Mediterranean motif and the chronology of type IA kaptorgas in Bohemia, the die can be dated to the 10th and beginning of the 11th century. X-Ray fluorescence analysis and elemental mapping of the object's surface show that it was made from bronze with a significant lead admixture and a small admixture of zinc. The die is discussed in terms of the spread of Mediterranean motifs and their adaptation by local craftsmen.