Miracle-dz/UniFAR-FTUs huggingface dataset:
PROBLEMS AND PROSPECTS OF FRUIT PROCESSING INDUSTRY: A STUDY WITH REFERENCE TO CHITTOOR DISTRICT OF ANDHRA PRADESH

This research study was designed to understand the cause and effect relationship between Counterproductive Work Behaviour (CWB) and Organization justice among junior managers (scale -1 officer) of Indian public sector banks. Total 300 junior managers (scale -1 officers) were chosen through purposive sampling technique from various Indian Public Sector Banks. Data was collected by questionnaire method and analyzed with structure equation modeling and Karl Pearson correlation. Result of research study reveals sabotage and withdrawal dimensions of CWB were positively and significantly correlated with organization justice. Theft another dimension of CWB was found positive and significantly correlated with procedural and interaction justice, dimensions of organization justice, among scale-1 officers of Indian Public Sector Banks. No significant relation were found between abuse, property deviance dimensions of CWB with organization justice.
Design of High Performance Microstrip LPF with Analytical Transfer Function

Abstract By exploiting butterfly and T-shaped resonators, a new design of microstrip lowpass filter (LPF) is proposed and analyzed. The LPF is investigated in four sections. Analyzing initial resonator and its equation in detail, providing a sharp skirt by using series configuration, suppressing in middle frequencies and suppressing in high frequencies are focused in each section, respectively. To present a theoretical design, LC equivalent circuit and transfer function are precisely calculated. The measured insertion loss of the LPF is less that 0.4 dB in frequency range from DC up to 1.25 GHz, and the return loss is better than 16 dB. A narrow transition band of 217 MHz and a roll-off rate of 170.5 dB /GHz are indicative of a sharp skirt. By utilizing T-shaped and modified T-shaped resonators in the third and fourth sections, respectively, a relative stopband bandwidth (RSB) of 166 % is obtained. Furthermore, the proposed LPF occupies a small circuit of 0.116λg×0.141λg$0.116{\lambda _g} \times 0.141{\lambda _g}$ ,where λg${\lambda _g}$ is the guided wavelength at cut-off frequency (1.495 GHz). Finally, the proposed LPF is fabricated and the measured results agree well with the simulated ones.
Connecting to Place, People, and Past: How Products Make Us Feel Grounded

Consumption can provide a feeling of groundedness or being emotionally rooted. This can occur when products connect consumers to their physical (place), social (people), and historic (past) environment. The authors introduce the concept of groundedness to the literature and show that it increases consumer choice; happiness; and feelings of safety, strength, and stability. Following these consequential outcomes, the authors demonstrate how marketers can provide consumers with a feeling of groundedness through product designs, distribution channels, and marketing communications. They also show how marketers might segment the market using observable proxies for consumers’ need for groundedness, such as high computer use, high socioeconomic status, or life changes brought on by the COVID-19 pandemic. Taken together, the findings show that groundedness is a powerful concept providing a comprehensive explanation for a variety of consumer trends, including the popularity of local, artisanal, and nostalgic products. It seems that in times of digitization, urbanization, and global challenges, the need to feel grounded has become particularly acute.
Modelling and Development of 4H-SiC Nanowire/Nanoribbon Biosensing FET Structures

A SiCNWFET device serving as a biosensor was designed and simulated using Silvaco ATLAS device simulation software. The performance of the designed device in charges sensing was investigated. The device shows the ability to recognize different interface charge values ranging from-1.10E11 to-5.10E12 cm-2 applied on the surface of the silicon carbide nanowire channel to simulate target charge biomolecules that bound to the biosensor. A significant change in the output current is observed due to the presence of different values of fixed interface charge densities. An optimum, according to the TCAD simulation, the 4H-SiC epitaxial structure has been grown. The designed device was fully fabricated on this structure and it exhibited acceptable electrical characteristics.
New Mobile Cloud Computing Approach Based Multi-Agent System For OWL-S Services

Using mobile cloud technology, local application resources can move into the cloud computing resource pool in the form of web services. The web services discovery and execution processes in the mobile environment are considered as a very difficult challenge. Moreover, these processes may degrade network performance due to the mobile environment. To overcome these issues, we present a new approach for better discovery, selection, execution, and negotiation of OWL-S services by utilizing a multi-agent system in mobile cloud computing. By using the Multi-Agent System (mobile agent and fixed agent), these processes are made with the minimum utilization of resources because the mobile agents migrate to targeted services and interact locally with them. Moreover, the use of mobile agent overcomes the problems related to the mobile environment and wireless devices. Besides, it automatizes the discovery, selection, execution, and negotiation of OWL-S services. The obtained results demonstrate the effectiveness of the proposed system. Moreover, we conclude that the mobile agent is a good solution to eliminate the problem of wireless devices and the mobile environment, and reduced the execution time of service discovery and invocation. Also, the finding indicates that cloud computing is a good solution to eliminate the problem of storage and execution in mobile devices. Besides, the context-aware provides a more accurate service selection.
Studies on the Performance of Granular Cement Mixed with Nanomodified Materials

Abstract Nanomodified granular cement has higher strength and durability and has a denser microstructure than traditional concrete. Nanomaterials have surface effects, filling effects, and nucleation effects, which can improve the microstructure of concrete. In order to obtain cement materials with better performance, this article will mix nano-sulfur dioxide (SiO2), nano-silica (NS), and nano-titanium oxide (NT) into granular cement to study the types and dosages of nanomaterials and the effect of curing systems on the particles. The influence of cement abrasion resistance, by adding nanomodified materials of different particle sizes to the granular cement, the cement made on the 14th and 28th days after its setting has been tested for its compression resistance, ductility deformation, and frost resistance. The experimental results show that the ductility and deformation ability of concrete mixed with nanoparticles has a more obvious effect on the ductility deformation of 30 nm NS concrete, but the effect on 30 nm NT concrete is not as significant as that of 28d nano-concrete with the optimal amount of ductility deformation. It can be seen that 15 nm NS is 6.3% higher than 30 nm NS, and 30 nm NS is 11.1% higher than 30 nm NT. This shows that, in order to play the role of the nanomodified material particle cement, it is necessary to carefully study and judge different projects in order to play a better role.
Recently Emerging Trends in Magnetic Polymer Hydrogel Nanoarchitectures

ABSTRACT Magnetic hydrogels (MHDG) are composites that are biocompatible, biodegradable, magnetically responsive, and characterized by type, concentration, geometry, and degree of uniformity of magnetic particulates, and hydrogels (HDG) used in fabrication. Nowadays, magnetically responsive smart hydrogels (MHDG) have been utilized in biomedicals and attainment of functional architectures. Furthermore, MHDG has been utilized as effective drug targeting and releasing tools. Hence, this paper gives brief insight into HDG evolution till the designing and development of MHDG; elaborates on MHDG relative to fundamental concepts concerning superparamagnetic iron oxide nanoparticulates, along with the fabrication and characterization of magneto-responsive HDG. Furthermore, critical uses of MHDG for drug conveyance, tissue engineering, cancer therapy, and environmental parameters are elucidated. This is capped with highlights on the challenges and future prospective of MHDG for 3-D and 4-D printing. Graphical Abstract
The Research on Tool-Chip Contact Length for Cutting Superalloy under High Pressure Cooling

Abstract High pressure cooling is a new cooling technology, which provides a certain technical support for cutting superalloy. In this paper, the theoretical model of the acting area and force of the coolant under different pressures were established. A theoretical model of the tool-chip contact length in cutting superalloy under high pressure cooling was established by the theory of material mechanics. Through theoretical research and simulation analysis, it is concluded that high pressure coolant can reduce the tool-chip contact length, and with the increase of coolant pressure, the contact length further decreases.
Translanguaging Interpretive Power in Formative Assessment Co-Design: A Catalyst for Science Teacher Agentive Shifts

ABSTRACT All learners bring ideas about science phenomena to classroom learning, including formative assessment tasks. Educators and scholars have long been interested in making school science, including assessment, more equitable and culturally meaningful for (bi)multilingual learners. Translanguaging is increasingly seen as an important assessment design principle in (bi)multilingual classrooms, including science classrooms. Despite the increasing popularity of translanguaging as a pedagogical and assessment tool, questions remain about how teachers co-design and interpret translanguaging on formative assessments when teachers do not share multiple linguistic resources with their students. This manuscript explores the journey of one experienced and highly qualified teacher, Emily, as she participates in a teacher-researcher co-design collaborative focused on inviting students to draw on and deploy translanguaging in science formative assessment. I qualitatively analyze illustrative conversations during the Reflect and Modify phase of four sequential (Trans)Formative Assessment Co-design (TAC) cycles. Findings point to the ways in which Emily began to develop translanguaging interpretive power to understand (bi)multilingual work as well as the confidence to lean into the knowledge she brought to the conversation. Ultimately, participation in collective conversations about (bi)multilinguals’ work supported Emily to expand her ideological stances into more concrete, agentive actions.
Human-Autonomous Devices for Finite Element Discrete Element Analysis of Geo Material Based on Digital Image Technology

Abstract Based on the theory of digital image processing, geometric vector transformation and the principle of automatic generation of finite element meshes, a finite element-discrete element analysis method for digital image of geotechnical engineering materials is proposed. Combining the digital image technology with the finite element-discrete element method (FDEM) coupling analysis method proposed by Munjiza, a FDEM analysis system is developed to characterize the real heterogeneity of rock mass, which provides a new way to model rock mass and study the fracture mechanism of rock mass from a meso-scopic point of view. With the help of digital image technology, the system obtains the real meso-structure of rock material from the image of rock section. With the help of mature mesh generation technology, it maps it to the FDEM computational grid, thus overcoming the shortcomings of the original FDEM in considering material heterogeneity. Using this system, the Brazilian disk splitting test is simulated numerically, and the real fracture process of granite under load is reproduced. And we examined how transparency and task type influence trustfulness, perceived quality of work during human-autonomous system interaction. The numerical simulation results show that the stress distribution of rock samples considering heterogeneity is asymmetric, and the micro-structure of rock has an important influence on the crack propagation and stress distribution in rock.
Outcomes and Hand Use of Reaching Attempts: Comparison of Infants at Risk for Developmental Disability and Infants With Typical Development

Background Infants at risk for developmental disabilities often show signs of motor delay. Reaching is a skill that can help us identify atypical motor trajectories in early infancy. Researchers have studied performance after onset of reaching, but none have followed infants at risk from pre-reaching to skilled reaching. Aims We assessed differences in reaching outcomes and hand use as reaching skill emerged in infants at risk for developmental disabilities and with typical development. Methods and Procedures We followed infants at risk for developmental disabilities (n = 11) and infants with typical development (n = 21) longitudinally as they developed reaching skill. Infants reached for a toy at midline while sitting in the caregiver’s lap. Video data were coded for reach outcome (miss, touch, partial grasp, and whole-hand grasp) and hand use (right, left, and bilateral). Outcomes and Results Infants at risk had a larger proportion of missed reaches across visits compared to infants with typical development. Infants at risk also showed less variability in hand use when grasping over the study period. Conclusion and Implications Our results provide information to support early differences in reaching performance to inform identification of typical and atypical developmental trajectories. Future studies should assess how the missed reaches are different and consider other quantitative measures of movement variability in infants at risk.
ECA-CBAM: Classification of Diabetic Retinopathy: Classification of diabetic retinopathy by cross-combined attention mechanism

Although there is no distinctive header, this is the abstract. Diabetic retinopathy is an ophthalmological disease that causes bleeding in the fundus and loss of vision due to damage to blood vessels in the retina. It is one of the main causes of vision loss in the world. To slow down the development of the disease, early screening of the eyeball is needed. This paper proposes a new method of classification, automatic screening and accurate diagnosis of diabetic retinopathy based on convolutional neural network. Specifically, five attention mechanisms such as BAM, CBAM, ECA, CA and SeNet are used to classify diabetic retinopathy. Through comparative experiments, it is found that ECA-CBAM cross-combination model has the best classification performance.
Multi-modal Intermediate Fusion Model for diagnosis prediction

The goal of the diagnostic prediction task is to predict what disease patients are likely to have at their next visit, based on their historical electronic medical records. Existing studies mainly conduct the prediction task by separately using discrete medical codes or clinical notes. However, few existing studies fuse multi-modal features from medical codes and clinical notes together for diagnostic prediction. Practically, using multiple modes of EHRs data can obtain more complete patient representation to improve the predictive performance of the model. Therefore, we proposed a Multi-modal intermediate Fusion Model (MFM) to predict patient diagnosis based on diagnostic codes and clinical notes. Specifically, MFM is mainly based on recurrent neural network to model data in different modes to extract effective features. Then, an intermediate fusion module is used to not only extract the global context information of data in each mode, but also capture the correlation between data in different modes. Finally, a multi-modal fusion matrix is generated for diagnosis prediction. Experimental results on a real dataset show that the proposed method improves the prediction performance compared with the baseline methods.
Speech Emotion Recognition Exploiting ASR-based and Phonological Knowledge Representations

Speech emotion recognition (SER) is a challenging problem due to the insufficient dataset. This paper deals with this problem from two aspects. First, we exploit two levels of speech representations for SER task, one for automatic speech recognition (ASR)-based representations and the other for phonological knowledge representations. Second, we use transfer learning, pre-train models and transfer knowledge from other large corpus for none-SER task. In our system, the whole model is divided into two parts: two-representation learning module and SER module. We fuse acoustic features with ASR-based and phonological knowledge representations which are both extracted from pre-trained models, and the fusion features are used in SER training. Then a novel multi-task learning approach is proposed where a shared encoder-multi decoder model is used for the phonological knowledge representation learning. The Conformer structure is introduced for the SER task, and our study indicates that Conformer is effective for SER. Finally, experimental results on IEMOCAP show that the proposed method can achieve 77.35 weighted accuracy and 77.99 unweighted accuracy respectively.
An Improved Crowd Aggregation Prediction Algorithm Based on ARMA

∗ The gathering of abnormal crowds has brought huge hidden dangers to public safety. Accurate prediction of abnormal crowd gathering can effectively prevent and reduce the risk of abnormal gathering, and support reasonable security response decisions. The traditional ARMA algorithm can only make smooth predictions based on past historical data, and cannot predict sudden crowd gathering events. In order to alleviate this problem, this paper proposes an improved ARMA prediction algorithm. By adding the important factor of activity events to perform regression analysis, the parameters of the traditional ARMA prediction algorithm can be adjusted and optimized, so that it can more accurately predict the abnormal clustering trend of people related to mass events in a designated area. The experimental results show the superiority of our algorithm.
Multi-view Network with Transformer for Point Cloud Semantic Segmentation

The input of most point cloud semantic segmentation networks is the reconstructed complete point cloud, but in practical application scenarios, the vision devices often capture single frame point cloud data. In order to better adapt to the actual segmentation requirements in dynamic scenes, this paper proposes an online incremental point cloud semantic segmentation method, which inputs the existing saved point cloud and the currently captured point cloud into the network to make up for the lack of information in the single frame point cloud. The Transformer structure is added to the network to strengthen the fusion of contextual information. Triple Loss is introduced in the feature space to distinguish different types of point clouds in a fine-grained manner. The experimental results show that compared with the benchmark MCPNet model, the proposed semantic segmentation model improves mIoU by 2.8% and mAcc by 7% on the S3DIS Area5 dataset, further improving the accuracy of point cloud semantic segmentation.
A high isolation quad‐channel microstrip diplexer based on codirectional split ring resonators

In this study, a novel microstrip diplexer with four channels is designed by using codirectional split ring resonators (CDSRRs). Since CDSRRs provide dual resonance behavior, dual‐band bandpass filter with two poles at each passband can be created by coupling identical CDSRRs to input/output ports. Based on this approach, quad‐channel diplexer can be designed by coupling two more CDSRRs in different electrical length to another output. Both filters are fed by similar feeding lines. High isolation can be observed between the output ports by means of CDSRRs. The designed quad‐channel microstrip diplexer was also fabricated and tested for experimental verifications. The measured results are in a good agreement with the simulated results. Center frequencies of the channels were measured at 2.12, 2.45, 3.90, and 4.48 GHz with the minimum insertion losses of 2.27, 2.88, 2.00, and 2.71 dB, respectively. Isolation was observed as better than 44 dB from DC to 6 GHz.
A Common Software Development Framework For Coordinating Usability Engineering and Software Engineering Activities

Currently, the Usability Engineering (UE) and Software Engineering (SE) processes are practiced as being independent of each other. However, several dependencies and constraints exist between the interface specifications and the functional core, which make coordination between the UE and the SE teams crucial. Failure of coordination between the UE and SE teams leads to software that often lacks necessary functionality and impedes user performance. At the same time, the UE and SE processes cannot be integrated because of the differences in focus, techniques, and terminology. We therefore propose a development framework that incorporates SE and UE efforts to guide current software development. The framework characterizes the information exchange that must exist between the UE and SE teams during software development to form the basis of the coordinated development framework. The UE Scenario-Based Design (SBD) process provides the basis for identifying UE activities. Similarly, the Requirements Generation Model (RGM), and Structured Analysis and Design are used to identify SE activities. We identify UE and SE activities that can influence each other, and identify the high-level exchange of information that must exist among these activities. We further examine these interactions to gain a more in-depth understanding as to the precise exchange of information that must exist among them. The identification of interacting activities forms the basis of a coordinated development framework that incorporates and synchronizes the UE and SE processes. An examination of the Incremental and Spiral models as they relate to the SBD is provided, and outlines how our integration framework can be composed. Using the results of and insights gained from our research, we also suggest additional avenues for future work.
Stated Preference Economic Development Model

Abstract : The United States Government has provided over $51 billion in aid to Afghanistan since 2002. There are a lack of data and methods to determine the net social benefit of this aid. Additionally, currently available data are insufficient to properly prioritize the usage and award of this aid. SPED involved the creation of tools that estimate the net social benefit of projects using cost-benefit techniques referred to as contingent valuation methods (CVM). Additionally, SPED estimated the net social benefit of several different types of development projects in Afghanistan.SPED was a joint effort with the U.S. Army Human Terrain System (HTS) and involved a significant survey effort in Afghanistan that produced an empirical dataset showing how different population groups value several different classes of development projects. However, the studys methodology can be tailored to value any set of nonlethal actions. SPED can help strategic, operational, and tactical commanders to prioritize development aid; estimate the impact of nonlethal actions on civilian attitudes; determine the net social benefit of projects or programs; and validate subjective information on population priorities that is obtained through existing channels.