Miracle-dz/UniFAR-FTUs huggingface dataset:
Effects of Topological Parameters on Thermal Properties of Carbon Nanotubes via Molecular Dynamics Simulation

Due to their unique properties, carbon nanotubes (CNTs) are finding a growing number of applications across multiple industrial sectors. These properties of CNTs are subject to influence by numerous factors, including the specific chiral structure, length, type of CNTs used, diameter, and temperature. In this topic, the effects of chirality, diameter, and length of single-walled carbon nanotubes (SWNTs) on the thermal properties were studied using the reverse non-equilibrium molecular dynamics (RNEMD) method and the Tersoff interatomic potential of carbon–carbon based on the Large-scale Atomic/Molecular Massively Parallel Simulator (LAMMPS). For the shorter SWNTs, the effect of chirality on the thermal conductivity is more obvious than for longer SWNTs. Thermal conductivity increases with increasing chiral angle, and armchair SWNTs have higher thermal conductivity than that of zigzag SWNTs. As the tube length becomes longer, the thermal conductivity increases while the effect of chirality on the thermal conductivity decreases. Furthermore, for SWNTs with longer lengths, the thermal conductivity of zigzag SWNTs is higher than that of the armchair SWNTs. Thermal resistance at the nanotube–nanotube interfaces, particularly the effect of CNT overlap length on thermal resistance, was studied. The simulation results were compared with and in agreement with the experimental and simulation results from the literature. The presented approach could be applied to investigate the properties of other advanced materials.
Secure Supply Chain Management using RFID-IoT

Supply chain management is very much important in current implementation of Industry 4.0 applications. The production from the industries is transported to the customers through various intermediate systems. The monitoring and tracking of any resources throughout its end destination is much difficult to maintain the data especially for the raw commodities like ore, agricultural, metals where the loads are of uncountable but can be measurable through weights. RFID is a promising technology in tracking and the data is communicated to the cloud. The load sensors can be utilized along with microcontroller to send the real time data of the weight of the load carried during the transport. The RFID enables the tracking in support with GPS enabled technology. Security is possible via Blockchain that helps in the complete automatic tracking and monitoring the supply chain management. In this paper, a prototypic implementation of RFID-IoT in collecting data and the transactions are deployed by smart contracts in blockchain. The results show the hardware prototype that efficiently helps in monitoring of the load, transport and tracking of the intermediate stations through RFID-IoT and the security is highly enhanced by blockchain technique.
Resource allocation for D2D communication

There is provided a mechanism for allocating communication resources of a cellular communication network to a D2D communication. After an eNB has configured a number of resource pools indicating a set of resources usable in the D2D communication, D2D clusters which share a same resource pool are enabled to obtain resources for their respective D2D communication. By detecting the current resource utilization state in the allocated resource pool by measurement on the UE side, it is decided whether suitable resources are available or not. An overload situation is signalled to the eNB if no suitable resource can be detected.
Symbolic Reverence: An Ethnographic Study on the Tonggoluan and Pusi’ Death Rituals Within Bolaang Mongondow Society Through Victor Turner's Perspective

This ethnography study investigates the sociocultural significance of the Tonggoluan and Pusi’ death rituals that persist in Bolaang Mongondow society despite the threat of modernity. Current understanding ignores its ontological role in preserving the existence of Bolaang Mongondow, so this research aims to explain these traditions as a basis for identity formation and social reproduction through the lens of Victor Turner's symbolic anthropology. Using a rigorous ethnographic field study, data was collected through in-depth interviews and observation of six elders in Bolaang Mongondow. These findings reveal that Tonggoluan graves encapsulate the eternal spiritual connection between living and deceased ancestors. Its sacralization reflects a strong belief in a metaphysical realm that upholds the collective memory of this community. Meanwhile, wearing Pusi’ mourning clothes symbolizes sadness and passing down cultural values from generation to generation. This ritual also builds communal solidarity during mourning, reaffirming Bolaang Mongondow's identity. Essentially, these two traditions combine the temporary and the eternal through the creative reproduction of meaning, forming the basis of local existence. Therefore, maintaining this death ceremony amidst the erosion of modern culture is very important to ensure the continuity of the unique identity of this indigenous community. This encourages a deeper global appreciation of the role of death rituals in strengthening the cultural vitality of the Bolaang Mongondow community group.
Leaky Wave Slot Array Antenna Based on Gap Waveguide Technology with Cosecant Squared Pattern for 5G BTS Applications

This paper presents a novel leaky-wave antenna based on utilizing the high bandwidth and low loss ridge gap waveguide concept, featuring a cosecant squared radiation pattern. The antenna is designed to operate within the frequency range of 25 GHz to 29 GHz. At the center frequency of 28 GHz, the antenna achieves a maximum gain of 10 dBi. Additionally, at a frequency of 28.8 GHz, the antenna exhibits a maximum return loss of -16.9 dB. Moreover, the proposed leaky-wave antenna demonstrates the potential of the radiation technology for 5G systems by enabling scanning angles ranging from approximately 5° to 20° across the specified frequency range. This feature highlights the versatility and suitability of the antenna for various applications in 5G communication systems.
The BAR Score Predicts and Stratifies Outcomes Following Liver Retransplantation: Insights From a Retrospective Cohort Study

Liver retransplantation (reLT) yields poorer outcomes than primary liver transplantation, necessitating careful patient selection to avoid futile reLT. We conducted a retrospective analysis to assess reLT outcomes and identify associated risk factors. All adult patients who underwent a first reLT at the Medical University of Innsbruck from 2000 to 2021 (N = 111) were included. Graft- and patient survival were assessed via Kaplan-Meier plots and log-rank tests. Uni- and multivariate analyses were performed to identify independent predictors of graft loss. Five-year graft- and patient survival rates were 64.9% and 67.6%, respectively. The balance of risk (BAR) score was found to correlate with and be predictive of graft loss and patient death. The BAR score also predicted sepsis (AUC 0.676) and major complications (AUC 0.720). Multivariate Cox regression analysis identified sepsis [HR 5.179 (95% CI 2.575–10.417), p < 0.001] as the most significant independent risk factor for graft loss. At a cutoff of 18 points, the 5 year graft survival rate fell below 50%. The BAR score, a simple and easy to use score available at the time of organ acceptance, predicts and stratifies clinically relevant outcomes following reLT and may aid in clinical decision-making.
Vegetation cover change and its mechanism in northeast China based on SPOT/NDVI data

SPOT/NDVI time series data between 1998-2007 were selected to analyze the vegetation cover change in Northeast China and its mechanism. To furtherly remove the cloud contaminated images,the HANTS algorithm was used,and then the slope of one variable linear regression was used to indicate the dynamic variation of surface vegetation cover. The results showed that the greening area was larger than the degraded area in Northeast China during recent 10 years,and the degraded severely areas mainly included the Hulun Buir,Xing 'an League,Tongliao city,Akane of inner Mongolia,especially Hulun Buir and Horqin.
The Transabdominal Lumbar Approach (TALA) for Robotic Renal Surgery—A Retrospective Single-Center Comparative Study and Step-by-Step Description of a Novel Approach

Simple Summary Robotic kidney cancer surgery is commonly performed by two different approaches: the transperitoneal approach (TP) and the retroperitoneal approach (RP). Both methods have challenges, such as limited space (RP) or difficulties in dissecting the renal artery (TP). A combination of both methods, called a hybrid approach, has been described before but not fully evaluated. The study proposed a new modified hybrid approach called the transabdominal lumbar approach (TALA). The study compared 20 consecutive patients undergoing RP and 20 patients using TALA. The study looked at factors such as operation time, blood loss, and complications. The study found that both methods were similar in most areas. In conclusion, TALA is a safe and promising approach that combines the benefits of RP and TP for kidney cancer surgery. Abstract The transperitoneal approach (TP) and the retroperitoneal approach (RP) are two common methods for performing nephrectomy or partial nephrectomy. However, both approaches face difficulties, such as trocar placement and limited working space (RP). TP is impaired in the case of dorsal tumors and dissection of the renal artery can be challenging due to the anatomic localization dorsally to the renal vein. A hybrid approach that combines both methods has been previously reported in a case series, but not evaluated systematically. This study proposes a modified hybrid approach, which we call the transabdominal lumbar approach (TALA), involving late robotic docking after elaborating the retroperitoneum using conventional laparoscopy. The study compares the last 20 consecutive patients who underwent RP and the last 20 patients who underwent TALA at our institution. The investigated variables include operative time and amount of blood loss, hospitalization duration, postoperative analgesia requirement, and postoperative complications. The study found no significant difference in operative time, blood loss, ischemia time, or hospital stay between the two groups. The TALA group had fewer complications regarding Clavien–Dindo category 3, but one complication of category 4. In Conclusion, TALA is a safe and promising approach that combines the advantages of RP and TP.
A Dynamic Method To Identify New Fields Of Scientific Research: An Application To Bioenergy

The purpose of this study is to detect emerging areas of research on Bioenergy using a method based on topological measures applied to scientific publication networks. This paper presents a methodological effort to deal with a data base of papers related to bioenergy using key words without the definition of filters previously applied. The data was collected from the Institute for Scientific Information (ISI) through the Web of Science (WoS) database. As a result, 244,307 scientific articles were obtained. The results of the research reveals one cluster has emerged in recent years; however, it also shows that this is not homogenous. So, it was performed a new clusterization that considered only the papers from the emergent cluster. This analysis allows to achieve an emergent sub-cluster clearly identified with the themes of bioenergy. The emergent sub-cluster brings together studies from bioenergy and third-generation biofuel sustainability, two areas that also represent cutting-edge research.
Dynamic Price Personalization: Predicting the Optimum Price to Maximize Revenue

In an advanced digital society, retailers have been personalizing their product proposals and advertisements in order to capture consumer needs at the right timings. However, they have not yet conducted personalization in price, which is also an important element in marketing. The purpose of the research is to design a personalization framework of the optimum pricing. We developed a joint model of store visit and product purchase for all customers in a nested logit model with hierarchical Bayesian framework, then the individual optimum prices are dynamically back calculated with results obtained from the nested logit model. With scanner panel data of retail stores during 2019/1/2-12/31 in Tokyo, the optimum price for a ketchup product was estimated for 569 customers simultaneously using the Markov Chain Monte Carlo (MCMC) Metropolis-Hastings algorithm. We also demonstrated a general dynamic pricing model and price density on a daily basis as a bottom-up approach of combining the optimum prices from all customers. Personal pricing simulation results indicated to increase approximately 8.6% revenue than that from the actual pricing. The personal optimum price prediction proposed in this research is an example of resource-based process and introduced as one of most efficient utilization of Big Data in marketing.
Gene Expression of Biofilm Regulatory Protein A (Brp A) in Streptococcus mutans Isolated from Oral Cavity

A total of 100 oral swabs were collected from patients suffering from dental caries and priodontal infections, ranging from 15-65 years old of both genders whom admitted to the Al-Diwaniyah Teaching Special Center of Dentistry within the period from December 2012 to March 2013, in order to quantify the gene expression of biofim regulatory protein (Brp A) in Streptococcus mutans (S. mutans) isolates by using the Real Time polymerase chain reaction. The gene expression of biofilm regulatory protein A(Brp A) was quantified in comparison with housekeeping gene 16s rRNA as a reference gene of biofilm S.mutans by using reverse transcriptase polymerase chain reaction (RT-PCR). The results revealed that the expression (absolute) of BrpA gene is decreased in the test treatment (S.mutans with 1% glucose+ 50% curcumine) in comparison with control (S.mutans grown in 1% glucose only). In conclusion, the present study established the role of Brp A gene in biofilm formation and recommended to possibility of using the curcumine as adddative material in composition of toothpaste due to their inhibitory and reduction effect on biofilm S.mutans isolates.
A static wireless charging position detection system for electric vehicles based on four-coil decoupling

When parking an electric vehicle, the misalignment between the transmit-ting coil and the pickup coil can cause a drop in power transfer, so it is necessary to provide the driver with the current accurate position of the vehicle to ensure the power transfer process. In this paper, a four-coil decoupling-based position detection method for electric vehicles is proposed to achieve complete decoupling between the transmitting coils by adding a set of de-coupling coils, and to determine the vehicle position information by detecting the transmitting coil current values. The simulation results show that the vehicle position can be effectively determined in the range of -12cm~12cm in each of X and Y axes.
Wideband Reconfigurable BOR Antenna Compound

A low-profile wideband reconfigurable antenna compound is investigated, where the height above the ground plane is less than 0.09 wavelength at the operating lowest frequency. The compound is composed of a fed BOR (body of revolution) and multiple parasitic elements printed on a thin dielectric substrate. The terminal point of each parasitic element is connected to the ground plane through an on-off switching circuit. The omnidirectional beam generated from the BOR can be tilted in the elevation plane and steered in the azimuth plane by changing on-off state of the parasitic elements. The proposed compound operates across a wide frequency band of approximately 35%.
Junction-Optimized SPAD With 50.6% Peak PDP and 0.64 cps/μm2 DCR at 2 V Excess Bias Voltage in 130 nm CMOS

This letter presents a frontside-illuminated single-photon avalanche diode (SPAD) with high peak photon detection probability (PDP), low dark count rate and low jitter. A retrograde doped and separated deep n-well (DNW) combined with a junction-optimized p-well within the photosensitive region achieves an STI-free structure, significantly minimizing the dark count rate caused by the etching traps and surface states. The visible spectrum’s high PDP is realized through the wide depletion region generated between the carefully modulated p-well and the DNW. Through a globally shared DNW structure, a <inline-formula> <tex-math notation="LaTeX">${16}\times {8}. {5}\,\,\mu \text{m}$ </tex-math></inline-formula> SPAD array is fabricated and characterized in a 130 nm CMOS process. The measured median breakdown voltage is 16.08 V. The proposed SPAD has a peak PDP of 50.6%, a DCR of 0.64 cps/<inline-formula> <tex-math notation="LaTeX">$\mu \text{m}^{{2}}$ </tex-math></inline-formula>, an afterpulse probability of 0.16%, and a jitter of 56 ps at an excess bias voltage of 2 V. Therefore, the proposed structure shows excellent potential for time-gated time-of-flight (ToF) and high dynamic range image sensor applications.
The principal stress of soil in the direction of plane strain

The principal stress of soil in the direction normal to plane strain is usually considered to be the intermediate principal stress,however it is true only when the sample is nearly failed in plane strain condition. In present paper, based on test results and theory analysis, some interacting conclusions are drawn. In the plane strain loading tests where the ratio of major active principal stress to minor one keeps a small constant, the principal stress of soil in the direction normal to plane strain is generally the minor principal stress. In the plane strain tests where active principal stresses decrease to small values, the principal stress of soil in the direction normal to plane strain may become the major principal stress, that indicates the yielding of soil under decreasing load and results from elasto plasticity of soils.
A Comprehensive Analysis of Chronic Health Diseases using Big Data

In recent times, individuals have been confronted with a multitude of health diseases as a result of their living environments and the prevailing environmental conditions. A disease that lasts for over three months is categorized as a chronic disease, and it is projected to become the primary global cause of mortality.A chronic ailment progresses slowly, leading to damage in the body. The circumstances could potentially respond to medical treatment, or they might not. The chronic disease can be managed, but neither medicines nor vaccines can cure it. Chronic disease is mainly divided into various types such as cancer, heart disease, diabetes, asthma, Parkinson’s disease, arthritis, rheumatoid, stroke, and kidney disease. Identifying and diagnosing chronic diseases in their early stages is of paramount importance, yet it remains a challenging task for doctors to accurately detect and treat these conditions. Thegoalof this research is to create a model with high interpretability for predicting and diagnosing chronic diseases. The analytics of big data plays a significant role in treating and predicting chronic diseases. This analytics enables higher accuracy results, effectiveness, and less computational and time complexity, as demonstrated in this survey. The goal of this study is to create a model with high interpretability for predicting future diagnosis.
Topic-Based Search: Dataset Search without Metadata and Users’ Knowledge about Data

With the advancement of information technologies, we can obtain various kinds of data, which can be leveraged for various purposes. The availability of a large amount of data is a desirable situation. However, it makes dataset retrieval a time-consuming and complex task. Conventional dataset search methods require unified metadata and knowledge about keywords representing the datasets. In other words, they require user knowledge regarding the datasets, such as the terms used in the dataset and fields in the metadata. To address this issue, we propose a topic-based search method without metadata, especially for users lacking knowledge about the datasets. The topic-based search can find datasets by using not the exact keywords but abstract keywords described as topics. In this paper, we focus on table data, which contain column names and data values and are widely used for storing data. As preliminary analysis, we collected and analyzed public datasets available in Japanese data portals to clarify the features of datasets that should be searched through dataset search. The analysis results revealed the use of many general and common keywords as column names, but it is difficult to implement a dataset search using only column names. Therefore, based on the analysis results, we decided to use embeddings converted from the datasets to utilize both column names and data values to extract topics from datasets. The experimental results showed that we can extract topics from datasets by using the topic modeling method and obtain better search results when compared with the search method using exact keywords.
Evaluation of the shear transfer mechanisms in reinforced concrete beams using photogrammetry

The models to predict the shear behavior in reinforced concrete (RC) members are still far from be consensual. Thus, a detailed understanding of the physical phenomenon and a detailed monitoring of shear tests on RC members is fundamental. Identify and quantify separately the contribution of each component of the shear transfer mechanism it is a challenge. The traditional instrumentation usually results in the evaluation of a limited number of sections. Additionally, technologies based on image analysis have been applied to structural monitoring with excellent results. In this paper, the method Photo‐Shear, developed to monitoring shear tests based on photogrammetry, is presented. The method allows a better understanding of the shear strength mechanism by acquiring data from the surface of RC members. Then, postprocessing procedures leads to outputs with the redundancy and complementarity necessary to characterize: (a) displacement and strain fields; (b) overall shear deformation (distortion and rotation); (c) load path and direction of the compression strut; (d) shear cracks' characterization; and (e) the aggregate interlock effect. The method was validated by monitoring two RC beams tests. Based on the results obtained, several advantages of the proposed Photo‐Shear method were demonstrated over the traditional instrumentation, namely, the quantity and quality of the information obtained, and the redundancy and complementarity of the results analyzed.
A Review of Neural Network Lightweighting Techniques

The application of portable devices based on deep learning has become increasingly widespread, which has made the deployment of complex neural networks on embedded devices a hot research topic. Neural network lightweighting is one of the key technologies for applying neural networks to embedded devices. This paper elaborates and analyzes neural network lightweighting techniques from two aspects: model pruning and network structure design. For model pruning, a comparison of methods from different periods is conducted, highlighting their advantages and limitations. Regarding network structure design, the principles of four classical lightweight network designs are described from a mathematical perspective, and the latest optimization methods for these networks are reviewed. Finally, potential research directions for lightweight neural network pruning and structure design optimization are discussed.