Miracle-dz/UniFAR-FTUs huggingface dataset:
Experimental and numerical investigation of an adaptive simulated annealing technique in optimization of warm tube hydroforming

Simulated annealing technique – which has attracted significant attention as being suitable for combinatorial optimization problems – has been used in many engineering applications. In current research, this method is used in optimization of a complicated forming process. Warm tube hydroforming is a new technology in the forming of lightweight aluminum and magnesium alloys in automotive, electronics and leisure industries. Owing to the complex nature of this process at high temperatures, and difficulty of obtaining the optimized forming conditions, this process has not received the credit it deserves yet. A new method for optimization of the warm tube hydroforming process is developed by using the simulated annealing algorithm with a novel adaptive annealing schedule. The optimal pressure loading paths are obtained for AA6061 aluminum alloy tubes with different wall thicknesses and corner fillets. The results obtained by simulated annealing technique are verified numerically and experimentally.
Application of data mining in science and technology management information system based on WebGIS

With the rapid development of science and technology and the quick increase of information, a great deal of data is accumulated in the management department of science and technology. Usually, many knowledge and rules are contained and concealed in the data. Therefore, how to excavate and use the knowledge fully is very important in the management of science and technology. It will help to examine and approve the project of science and technology more scientifically and make the achievement transformed as the realistic productive forces easier. Therefore, the data mine technology will be researched and applied to the science and technology management information system to find and excavate the knowledge in the paper. According to analyzing the disadvantages of traditional science and technology management information system, the database technology, data mining and web geographic information systems (WebGIS) technology will be introduced to develop and construct the science and technology management information system based on WebGIS. The key problems are researched in detail such as data mining and statistical analysis. What's more, the prototype system is developed and validated based on the project data of National Natural Science Foundation Committee. The spatial data mining is done from the axis of time, space and other factors. Then the variety of knowledge and rules will be excavated by using data mining technology, which helps to provide an effective support for decisionmaking.
Continual reelin signaling by the prime neurogenic niche of the adult brain

During development reelin sets the pace of neocortical neurogenesis enabling in turn newborn neurons to migrate, but whether and, if so, how reelin signaling affects the adult neurogenic niches remains uncertain. We show that reelin signaling, resulting in Dab1 phosphorylation, occurs in the ependymal-subependymal zone (EZ/SEZ) of the lateral ventricles where, along with its associated rostral migratory stream (RMS), the highest density of functional ApoER2 accumulates. Mice deficient for reelin, ApoER2 or Dab1 exhibit enlarged ventricles and dysplastic RMS. Moreover, while the conditional ablation of Dab1 in neural progenitor cells (NPCs) enlarges the ventricles and impairs neuroblasts clearance from the SEZ, the transgenic misexpression of reelin in NPCs of reelin-deficient mice normalizes the ventricular lumen and the density of ependymal cilia, ameliorating in turn neuroblasts migration; consistently, intraventricular infusion of reelin reroutes neuroblasts. These results demonstrate that reelin signaling persists sustaining the germinal niche of the lateral ventricles and influencing neuroblasts migration in the adult brain.
OptDesign: Identifying Optimum Design Strategies in Strain Engineering for Biochemical Production

Computational tools have been widely adopted for strain optimisation in metabolic engineering, contributing to numerous success stories of producing industrially relevant biochemicals. However, most of these tools focus on single metabolic intervention strategies (either gene/reaction knockout or amplification alone) and rely on hypothetical optimality principles (e.g., maximisation of growth) and precise gene expression (e.g., fold changes) for phenotype prediction. This paper introduces OptDesign, a new two-step strain design strategy. In the first step, OptDesign selects regulation candidates that have a noticeable flux difference between the wild type and production strains. In the second step, it computes optimal design strategies with limited manipulations (combining regulation and knockout) leading to high biochemical production. The usefulness and capabilities of OptDesign are demonstrated for the production of three biochemicals in E. coli using the latest genome-scale metabolic model iML1515, showing highly consistent results with previous studies while suggesting new manipulations to boost strain performance. Source code is available at https://github.com/chang88ye/OptDesign.
A parametrized computational framework for description and design of genetic circuits of morphogenesis based on contact-dependent signaling and changes in cell-cell adhesion

Synthetic development is a nascent field of research that uses the tools of synthetic biology to design genetic programs directing cellular patterning and morphogenesis in higher eukaryotic cells, such as mammalian cells. One specific example of such synthetic genetic programs was based on cell-cell contact-dependent signaling using synthetic Notch pathways, and was shown to drive formation of multilayered spheroids by modulating cell-cell adhesion via differential expression of cadherin-family proteins. The design method for these genetic programs relied on trial and error, which limited the number of possible circuits and parameter ranges that could be explored. Here we build a parametrized computational framework that, given a cell-cell communication network driving changes in cell adhesion and initial conditions as inputs, predicts developmental trajectories. We first built a general computational framework where contact-dependent cell-cell signaling networks and changes in cell-cell adhesion could be designed in a modular fashion. We then use a set of available in vitro results (that we call the “training set” in analogy to similar pipelines in the machine learning field) to parametrize the computational model with values for adhesion and signaling. We then show that this parametrized model can qualitatively predict experimental results from a “testing set” of available in vitro data that varied the genetic network in terms of adhesion combinations, initial number of cells and even changes to the network architecture. Finally, this parametrized model is used to recommend novel network implementation for the formation of a 4-layered structure that has not been reported previously. The framework that we develop here could function as a testing ground to identify the reachable space of morphologies that can be obtained by controlling contact-dependent cell-cell communications and adhesion. Additionally, we discuss how the model could be expanded to include other forms of communication or effectors for the computational design of the next generation of synthetic developmental trajectories.
Study on rowing athlete selection potential based on stepwise regression analysis

A coach usually selects potential athletes based on their performances in competition or daily routine training, which is not that scientific to some degree. By taking long distance rowing as an example and establishing potential model, this paper provides coach a way to select athletes based on stepwise regression analysis and type analysis. We get our results through the analysis of collected data and the test of the program most related to the sport and the results are most related to the scores in completion, and by type analysis, we rate the athletes into three levels. A curve line is made according to the performance of athlete and calculate the slope when the athlete’s performance is basically stable, which is the potential value of the athlete. We select the athlete of greatest value in a certain type according to their levels who has the potential to achieve better results.
GaInAsP/InP quantum-wire lasers and distributed reflector lasers with wirelike active regions by lithography and regrowth

For high performance operation of semiconductor lasers consisting of low-dimensional electron systems as the active medium, a good size uniformity and a formation of low-damage interfaces are essentially required. In this paper, we review our recent results obtained by GaInAsP/InP based long-wavelength lasers consisting of quantum-wire structures fabricated by electron beam lithography, CH4/H2-reactive ion etching and 2-step organo-metallic vapor-phase-epitaxial growth processes. Good size uniformity of vertically-stacked multiple-quantum-wire structures was obtained with a standard deviation of less than ±2 nm. By using a strain-compensated quantum-well structure as an initial wafer, non-radiative recombinations at etched/regrown interfaces were fairly reduced, which resulted in a room-temperature continuous-wave (RT-CW) operation of a quantum-wire laser for more than 15,000 hours. By taking an advantage of this fabrication method, 1540 nm wavelength quantum-wire distributed feedback (DFB) lasers were also realized for the first time with relatively low threshold current and high differential quantum efficiency under a RT-CW condition. Moreover, by utilizing the energy blue shift due to the lateral quantum confinement effect, a low threshold current operation with a stable single-mode property has been successfully demonstrated for distributed-reflector (DR) lasers consisting of a DFB section with wirelike active regions and a passive distributed-Bragg-reflector (DBR) section with narrow quantum-wire active regions.
Study of low-dose-rate radiation effects on commercial linear bipolar ICs

The results of a detailed study of the degradation of commercial linear bipolar ICs due to irradiation at four dose rates are presented. The time dependence of the degradation rate at the different dose rates is shown to be consistent with a model that describes a mechanism for defect generation in the devices used in this study. Based on this model, an accelerated test procedure for bipolar devices is proposed.
APPLICATION OF DRAINMOD–N TO FIELDS WITH IRREGULAR DRAINAGE SYSTEMS

Subsurface drainage systems are a significant source of nitrate pollution to surface water supplies in the flat watersheds of East Central Illinois. Many of these watersheds are drained exclusively by subsurface tile and ditch flow. To solve localized drainage problems, many tile drainage systems were installed with an irregular or random design. The purpose of this study is to apply DRAINMOD–N to irregular tile systems and develop a methodology to determine the effective drain spacing of irregular drain systems based on system geometry and effective drainage area of isolated tile lines. This study also examines the application of a cell–based DRAINMOD–N with surface runoff routing to model flow in fields with irregular systems. DRAINMOD–N was used to model tile flow and nitrate load from two monitored, irregular tile systems. The results of this study show that over a 2–year calibration period, for Drummer soil type, the effective lateral distance of influence for individual tile lines is 18.3 m. The average daily flow deviation between observed and simulated flow was 1.2 mm/day. Cell–based analysis with surface routing of irregular tile systems provided a lower deviation (0.96 mm/day). The results of the nitrate experiment showed an average monthly deviation of 3.02 kg/ha–N.
A pilot study of psycho social intervention program for the children of migrant workers and the potential role of self- efficacy in promoting mental health

The history of migration is old as the origin of human life. Along with the colourful dreams, the struggles and huddles during the period of migration can directly or indirectly affect the self-efficacy and mental health of the children. The purpose of this study was to develop an intervention program for children of migrant workers to strengthen their self-efficacy and promote their mental health as well as to do the pilot test to know its vitality, usability and sustainability. The combination of qualitative and quantitative research designs was having great role in the development of this intervention program. Self-Efficacy Scale (SES) and Mental Health Battery (MH) were used to measure the level of self-efficacy and mental health of the participants. Focusedgroup discussions were carried out to get a better understanding about the real situation and problems of the children of migrant workers. The intervention program was prepared based on the four dimensions of self-efficacy as well as the culture, life situations and back ground of the respondents. Pilot test of this intervention program was conducted among 65 children of migrant workers. The participants actively participated and positively responded to the program. The result of the pilot test proved the improvement in the level of self-efficacy and mental health of the participants.
Don't Bite the Bait: Phishing Attack for Internet Banking (E-Banking)

Phishing attacks are based on obtaining desired information from users quickly and easily with the help of misdirection, panic, curiosity, or excitement. Most phishing websites are designed on internet banking(e-banking), and the attackers can acquire ﬁnancial information of misled users with the tactics and discourses they develop. Despite the increase of prevention techniques against phishing attacks day by day, an eﬀective solution could not be found for this issue due to the human factor. Because of this reason, attackers’ attack techniques and strategies from actual phishing attacks are essential to study and analyze. This study focused on the detection and analysis of a real e-banking phishing attack using the phishing website. Analysis results show that the attacker’s information is traceable.
MODELLING AN INSIDER THREATS DETECTION METHOD AGAINST EMAIL CONTENT

An insider threats has become one of the most challenging malicious activity in cybersecurity defense compared system recently. Since an insider threats usually expand and spread internally, no one could predict what, when and how exactly malicious insider launched their attacks. This is in a view of fact that an email becomes one of the primary targets of an internal threats as this medium widely used by everyone to communicate, share, and exchange confidential information. Therefore, it is extremely important to understand the nature of insider threats behavior beforehand and construct an accurate detection model. Furthermore, every single keyword used in an email can reflect the behavior of an individual and can be used to determine their intentions i.e., have motive to launch an insider threat or not. Henceforth, an innovative approach is proposed in modelling an insider threats detection in this work. In addition, various statistical analysis i.e., scoring, Friedman, linear regression (R2) and correlation coefficient applied to analyze an insider threat relationship among historical insider threats behavior and relevant extracted keywords from an email content. The Friedman statistical used to determine the minimum differences between each extracted insider threats keywords that represent different insider threats factor (motive, opportunity, capability). Besides, linear regression applied to estimate the relationship of an insider threats from training keywords and testing keyword with allocate anomaly score. Finally, the correlation coefficient approach used to determine how strong a relationship is between extracted insider threats keywords and insider threats behavior in this research. The proposed modelling approach has been evaluated using the benchmark dataset known as CERT that comprises malicious email file. Throughout the experiment, the proposed insider threats detection approach has achieved higher attack detection rate as well as minimized undetectable insider threats behavior as compared to previous researcher works.
A 10-14 GHz linear MMIC vector modulator with less than 0.1 dB and 0.8 degrees amplitude and phase error

The design, fabrication, and performance of a GaAs monolithic linear vector modulator in the 10-14 GHz band is described. The circuit exhibits sideband and carrier rejections of more than 45 dB with third-order intermodulation signals at -40 dBc. Such performance has never been obtained in hybrid or monolithic technology. The design is based on symmetrical circuits. The vector modulator comprises two monolithic binary-phase-shift keying (PSK) modulators, a monolithic quadrature power divider, and a Wilkinson power combiner. The modulator is ideal for direct 16-quadrature amplitude modulation (QAM) in X-Ku-band digital radio links and satellite communications. Due to its linearity, amplitude, and phase precision, it has numerous applications, such as for an analog phase shifter for phased-array antennas or for a single-sideband up converter. <<ETX>>
Settling control and performance of a dual-actuator system for hard disk drives

This paper presents a settling control of a dual-actuator system for hard disk drives. The dual-actuator system consists of a voice coil motor (VCM) as a first stage actuator and a push-pull-type piezo-electric transducer (PZT) as a second-stage actuator. The settling controller is designed in three steps. In the first step, the VCM controller is designed so that the VCM feedback loop has basic performance and appropriate stability. In the second step, the PZT controller and a decoupling filter are designed in order to achieve superior performance of the dual-actuator system. The decoupling filter, which is placed between the PZT controller output and the VCM controller input, is a PZT output estimator so that the PZT actuator output is canceled at the VCM controller input. In the third step, the reference trajectory is designed for fast and smooth settling. In this study, the closed-loop sensitivity function is used as a performance index, and the gain and phase margins of the open-loop characteristic are used as stability measures. Experimental results show that the dual actuator system with the proposed settling controller achieves better performance than a single actuator system with the same VCM and a conventional settling controller.
ANTIOXIDATIVE ACTIVITY AND BER APPEARANCE IN PEPPER FRUITS UNDER INFLUENCE OF BIOSTIMULANT TREATMENT AND HYBRID

U ovom je istraživanju pracena antioksidativna aktivnost ploda paprike, ukupan i komercijalni prinos, broj nekomercijalnih plodova te pojava vrsne truleži ploda pod utjecajem tretmana s biostimulatorima i hibrida. Statisticki znacajno najveca (P≤0, 01) antioksidativna aktivnost, određena DPPH metodom, zabilježena je kod tretiranih biljaka paprike Century F1 te je bila u znacajnoj pozitivnoj korelaciji (0, 526*) s komercijalnim prinosom kod oba hibrida. Opcenito, tretman s biostimulatorima pozitivno je utjecao na sve ispitivane pokazatelje kod hibridne paprike Century F1, dok je znacajno smanjio pojavu nekomercijalnih plodova i vrsne truleži kod Blondy F1, sto je u konacnici dalo znacajno veci komercijalni prinos kod oba hibrida.
Deep Learning Algorithms based Fingerprint Authentication: Systematic Literature Review

Deep Learning algorithms (DL) have been applied in different domains such as computer vision, image detection, robotics and speech processing, in most cases, DL demonstrated better performance than the conventional machine learning algorithms (shallow algorithms). The artificial intelligence research community has leveraged the robustness of the DL because of their ability to process large data size and handle variations in biometric data such as aging or expression problem. Particularly, DL research in automatic fingerprint recognition system (AFRS) is gaining momentum starting from the last decade in the area of fingerprint pre-processing, fingerprints quality enhancement, fingerprint feature extraction, security of fingerprint and performance improvement of AFRS. However, there are limited studies that address the application of DL to model fingerprint biometric for different tasks in the fingerprint recognition process. To bridge this gap, this paper presents a systematic literature review and an insightful meta-data analysis of a decade applications of DL in AFRS. Discussion on proposed model’s tasks, state of the art study, dataset, and training architecture are presented. The Convolutional Neural Networks models were the most saturated models in developing fingerprint biometrics authentication. The study revealed different roles of the DL in training architecture of the models: feature extractor, classifier and end-to-end learning. The review highlights open research challenges and present new perspective for solving the challenges in the future. The author believed that this paper will guide researchers in propose novel fingerprint authentication scheme.
Heterogeneous Communication Architecture to Enable Demand Response Management for the Smart Grid

Demand response entails the control of the energy demand and loads during critical peak situations to achieve a balance between electrical energy supply and demand. A robust communication infrastructure, which consists of network components of Home Area Networks (HANs) and Neighborhood Area Networks (NANs) is the touchstone to achieve the demand response goals. This paper surveys existing communication technologies that can be adopted for demand response applications. A heterogeneous communication architecture based on Wireless Sensor Networks (WSNs) and Ethernet Passive Optical Networks (EPONs) is presented, and the reliability and scalability requirements of communication system is satisfied.
Forefront Office in Service Systems: Concept and Design

Conventionally, service systems have been considered to comprise two main offices: the front office and the back office. However, a new managerial office is needed to relate customers with technology as technology-based services play a critical role for customers prior to two main offices. Nevertheless, there is no attention to management of this new area. In this sense, this paper suggests a novel concept of the “forefront office” as the new area to represent service activities. The forefront office is defined as a service facility which allows customers to be provided with services by themselves using technology-based services prior to the front office. For design of the proposed forefront office, a modified service blueprint is proposed. Following on the design structure of the forefront office, three topologies of the forefront office are also proposed based on the modified service blueprint. The forefront office is expected to reduce labour costs and improve customer satisfaction in terms of mass customization.