Miracle-dz/UniFAR-FTUs huggingface dataset:
The Economic Dimension of Labour Migration Cauvery Delta Zone in Tamil Nadu, India

Abstract: Majority are international migrant and interstate migrants, majority (75%) of the respondents in the age groups (21 to 40) migrated to different places like Thiruppur, Coimbatore, Chennai, Kerala and Saudi, Arabia, Dubai, Mascot, Malaysia, and Singapore. Main reasons for migration are low wages, unemployment debt due to failure in agriculture due to lack of rains, more employment opportunities in the destination place and more jobs and a handsome salary which leads to improvement of the living conditions.Such pull and push factors encourage emigration to high-income countries experiencing labour shortages. Emigration has different impacts on sending country and destination country. Low wages and rain-fed agriculture in the native place have been found the economic factors leading to migration, while poverty, poor civic amenities, leading a poor life, high aspirations and demonstration effect were social and psychological factors resulting to migration. Lesser storage of water in delta region consequent on insufficient rainfall in the catchment area does not allow the farmers to Cauvery Delta Zone. Keywords: Labor migration, Employment, income and Cauvery Delta Zone
A Circuit-Compatible Model of Ballistic Carbon

Carbon nanotube field-effect transistors (CNFETs) are being extensively studied as possible successors to CMOS. Novel device structures have been fabricated and device simu- lators have been developed to estimate their performance in a sub-10-nm transistor era. This paper presents a novel method of circuit-compatible modeling of single-walled semiconducting CNFETs in their ultimate performance limit. For the first time, both the I-V and the C-V characteristics of the device have been efficiently modeled for circuit simulations. The model so devel- oped has been used to simulate arithmetic and logic blocks using HSPICE. Index Terms—Ballistic scaling, carbon nanotube (CNT), circuit- compatible model.
DDOS Detection using Attack Model

In today's world Distributed Denial of Service Attacks (DDoS) continue to pose a hazardous threat to cyber world. These attacks are still evolving and there is an utmost need to develop mechanisms which can be effective against them. It is however not easy to deal with such attacks. In this paper, we concentrate to develop attack model which gives us an idea about the patterns of the DDoS attacks. Our method maps flows of each attack pattern into an attack model. In this work we develop four types of attack models for the following DDoS attacks: Host scan, Port scan, TCP SYN flood, ICMP flood. Using these attack models we try to detect the above mentioned attacks by comparing the attack models with the incoming traffic. Keywords—Attack model, DDoS, Host Scan, Port Scan
An improved optimality criterion combined with density filtering method for structural topology optimization

The solid isotropic microstructure with penalization (SIMP) model is widely used in structural topology optimization. When the optimality criterion (OC) method is used for solving the SIMP model, the optimization solution process not only has relatively low computational efficiency, but also causes a large number of grey-scale elements in the obtained structure. To enhance the computational efficiency, an advance and retreat golden searching scheme is proposed to update the Lagrange multiplier, thereby improving the OC method for solving the SIMP model. To eliminate the grey-scale elements and also to enhance the computational efficiency, the improved OC method combined with the tanh-based density filtering is proposed for solving the SIMP model of structural topology optimization. Furthermore, the improved OC method combined with the sigmoid-based Heaviside density filtering is proposed for solving the SIMP model of multi-material structural topology optimization to eliminate the grey-scale elements and to enhance the computational efficiency.
PROSTATE ULTRASOUND IMAGE CLASSIFICATION USING CNN-BILSTM

Image classification task plays a vital role in the Computer-Aided Diagnosis system for diagnosis of prostate cancer. Transrectal Ultrasonography (TRUS) imaging techniques are mostly used by physicians to distinguish the prostate region from tissues around it and the same used for abnormality detection. The removal of irrelevant regions from the TRUS image is very rigid since TRUS images contain speckle noise, low dissimilarity, the fuzzy region between object and background, and also irregular form and size. To resolve the problem, the images are preprocessed by Ant Colony Optimization (ACO) method, and the relevant features are segmented by using Ant Colony OptimizationBoundary Complete Recurrent Neural Network (ACO-BCRNN). Then, VGG-19 transfer learning techniques are used to extract the Region of Interest (RoI) features. The relevant features are selected by using hybridization of the Salp Swarm Optimization Algorithm and Grasshopper Optimization Algorithm (SSOAGOA). In this article, Convolutional Neural Network with Bi-directional Long Short Term Memory (CNN-BiLSTM) is proposed for the classification task to distinguish the normal from abnormal image of prostate gland. The performance of the proposed method is assessed by using the classifiers such as Support Vector Machine (SVM), Grid Search (GS) and Extreme Machine Learning (ELM). The comparative analysis of proposed method is performed with CNN and CNN-LSTM. The result of the proposed method shows a significant gain in accuracy than other methods.
Phenotypic whole-cell screening identifies a protective carbohydrate epitope on Klebsiella pneumoniae

ABSTRACT The increasing global occurrence of recalcitrant multi-drug resistant Klebsiella pneumoniae infections warrants the investigation of alternative therapy options, such as the use of monoclonal antibodies (mAbs). We used a target-agnostic phage display approach to K. pneumoniae bacteria lacking bulky, highly variable surface polysaccharides in order to isolate antibodies targeting conserved epitopes among clinically relevant strains. One antibody population contained a high proportion of unique carbohydrate binders, and biolayer interferometry revealed these antibodies bound to lipopolysaccharide (LPS). Antibodies that bound to O1 and O1/O2 LPS were identified. Antibodies were found to promote opsonophagocytic killing by human monocyte-derived macrophages and clearance of macrophage-associated bacteria when assessed using high-content imaging. One antibody, B39, was found to protect mice in a lethal model of K. pneumoniae pneumonia against both O1 and O2 strains when dosed therapeutically. High-content imaging, western blotting and fluorescence-activated cell sorting were used to determine binding to a collection of clinical K. pneumoniae O1 and O2 strains. The data suggests B39 binds to D-galactan-I and D-galactan-II of the LPS of O1 and O2 strains. Thus, we have discovered an mAb with novel binding and functional activity properties that is a promising candidate for development as a novel biotherapeutic for the treatment and prevention of K. pneumoniae infections.
Inorganic CsSnI3 Perovskite Solar Cells: The Progress and Future Prospects

Although the power conversion efficiency of Pb‐based perovskite solar cells (PSCs) has increased rapidly from 3.8% to 25.2%, the concerns about the toxicity of Pb greatly hinders its large‐scale application in the future. Therefore, many efforts have been made to develop environmentally benign Pb‐free perovskites, and there is a growing consensus that Sn‐based perovskites are by far the most promising alternative due to their ideal electric and optical properties. Among Sn‐based perovskites, CsSnI3 perovskite shows great promise for developing high‐efficiency Sn‐based PSCs due to its high thermal stability, ideal bandgap range, and low exciton binding energy. On the basis of the device engineering, an efficiency up to 10.1% has been reported for CsSnI3 PSCs. Nevertheless, considering the theoretical efficiency of CsSnI3 PSCs to be over 30%, there is still much room for improvement in the efficiency. Herein, the properties of CsSnI3 perovskite are summarized and the origins of stumbling the efficiency improvement of CsSnI3 PSCs are provided. The device engineering toward more stable and efficient CsSnI3 PSCs is discussed in detail. Finally, the remaining challenges and future perspectives in the field of CsSnI3 PSCs are also shown to help further the development of highly efficient CsSnI3 PSCs.
Intrusion detection system and technology of layered wireless sensor network based on Agent

The intrusion detection system and technology of classified layered-wireless sensor network was able to meet the high safety requirements of wireless sensor network, it is urgent for us to improve the identification and generalization of detection system about characters of intrusion. In this paper, we design an intelligent intrusion detection system which realize intelligence, the effective and direct way was to add the methods, and it was used for identification and generalization of intrusion characters to the Agent function of intrusion detection. It could obtain credible judgment by updating and examining the database for the actions which the general misuse detection or anomaly detection were not sure if the intrusion was formed. DOI: http://dx.doi. org/10.11591/telkomnika.v11i8. 2347
The Multifaceted Role of Connexins in Tumor Microenvironment Initiation and Maintenance

Simple Summary Connexins are proteins which comprise gap junctions in cells. These junctions can directly connect neighboring cells and the cell interior with the extracellular microenvironment and thus they act as tissue integrators. Alterations in connexin regulation can lead to unfavorable shifts in the tissue adhesive context thus eradicating the constraints of the normal tissue microenvironment, triggering (or enhancing) cell motility. This review tries to examine the role of connexins in orchestrating the tumor microenvironment and hence their role in malignancy. Abstract Today’s research on the processes of carcinogenesis and the vital activity of tumor tissues implies more attention be paid to constituents of the tumor microenvironment and their interactions. These interactions between cells in the tumor microenvironment can be mediated via different types of protein junctions. Connexins are one of the major contributors to intercellular communication. They form the gap junctions responsible for the transfer of ions, metabolites, peptides, miRNA, etc., between neighboring tumor cells as well as between tumor and stromal cells. Connexin hemichannels mediate purinergic signaling and bidirectional molecular transport with the extracellular environment. Additionally, connexins have been reported to localize in tumor-derived exosomes and facilitate the release of their cargo. A large body of evidence implies that the role of connexins in cancer is multifaceted. The pro- or anti-tumorigenic properties of connexins are determined by their abundance, localization, and functionality as well as their channel assembly and non-channel functions. In this review, we have summarized the data on the contribution of connexins to the formation of the tumor microenvironment and to cancer initiation and progression.
Reliability Analysis of Cell Phone Use under Different Driving Conditions Based on Simulator

The impact of cell phone use on driving performance has been widely known yet is carried out to varying degrees under different driving conditions. 40 participants whose ages ranged from 23 to 25 took part in experiments on both highway and urban roads using a driving simulator. The experiment was carried out under five different conditions: 1) no call; 2) different phone types (hand-held or hands-free); 3) different conversation contents (casual or cognitive); 4) dialing; 5) texting messages. Driving performance indices such as speed maintenance, lane keeping, pedal force and displacement were monitored and analyzed. A reliability model of cell phone use under different driving conditions was established for the comprehensive analysis of different factors on driving performance. Results indicated that driving reliability decreased significantly despite the phone type and conversation content as the time of cell phone use increased, and frequent short-time cell phone conversation was more dangerous.
Hybrid force-position control of clamping with a piezo-stepper

The demands concerning shape accuracy, surface roughness, and subsurface damage on machined parts are continuously increasing. Traditionally, the production process of accurate and smooth surfaces consists of some roughing steps, like turning, and subsequent finishing steps, like polishing or precision grinding. Two new grinding processes, however, electrolytic in-process dressing (ELID), and high-speed chipping (HSC), can combine high removal rates with high surface quality through a mechanism of submicron chip removal. For the successful application of these processes, very stiff, ultra-precision positioning systems are needed. Classical solutions, based on traditional guide way technology, cannot meet the requirements of these new machining processes. The piezo-stepper solution presented in this paper can provide accurate motion, combined with high stiffness, through the use of piezo-electric actuators with high resolution. High passive stiffness is provided thanks to the integration of the driving, bearing and transmission functions. The same actuators can provide an extremely high active stiffness by referring the position of the positioning stage with respect to an absolute reference frame. In contrast with existing (position-controlled) piezo-steppers, this paper presents a way to provide smooth stepping by avoiding hammering through hybrid force-position controlled clamping and by rolling traction.
Autonomous decentralized manufacturing system using high-speed network with inductive transmission of data and power

This paper introduces an idea of an autonomous decentralized manufacturing system (ADMS), which has the capability of adaptive reconfiguration to the product variations. In ADMS, machines are decentrally controlled by way of common high speed data networks, and the degree of mechanical motion freedom is increased with the use of inductive power and data transmission. The technology subsets required for realizing the field network and inductive couplings are described in this paper. The ADMS is conceptually realized for the automobile production line using the prototypes of the proposed technology subsets.
Visual Map-based Localization applied to Autonomous Vehicles

This thesis is carried out in the context of Advanced Driver Assistance Systems, and especially autonomous vehicles. Its aim is to propose a method to enhance localization of vehicles on roads. I suggests using a camera to detect lane markings, and to match these to a map to extract the corrected position of the vehicle.The thesis is divided in three parts dealing with: the map, the line detector and the evaluation. The map is based on the OpenStreetMap data. The line detector is a based on ridge detection. The results are compared with an Iterative Closest Point algorithm. It also focuses on implementing the components under a real-time constraint. Technologies such as ROS, for synchronization of the data, and CUDA, for parallelization, are used.
A Hybrid Imputation Method for Multi-Pattern Missing Data: A Case Study on Type II Diabetes Diagnosis

Real medical datasets usually consist of missing data with different patterns which decrease the performance of classifiers used in intelligent healthcare and disease diagnosis systems. Many methods have been proposed to impute missing data, however, they do not fulfill the need for data quality especially in real datasets with different missing data patterns. In this paper, a four-layer model is introduced, and then a hybrid imputation (HIMP) method using this model is proposed to impute multi-pattern missing data including non-random, random, and completely random patterns. In HIMP, first, non-random missing data patterns are imputed, and then the obtained dataset is decomposed into two datasets containing random and completely random missing data patterns. Then, concerning the missing data patterns in each dataset, different single or multiple imputation methods are used. Finally, the best-imputed datasets gained from random and completely random patterns are merged to form the final dataset. The experimental evaluation was conducted by a real dataset named IRDia including all three missing data patterns. The proposed method and comparative methods were compared using different classifiers in terms of accuracy, precision, recall, and F1-score. The classifiers’ performances show that the HIMP can impute multi-pattern missing values more effectively than other comparative methods.
Medium-voltage power electronic technologies for future decentralized power systems

Increasingly, PWM voltage source inverters (VSIs) are being considered for medium-voltage power quality products. However, the high cost of PWM VSIs in comparison with classical thyristor based systems has hampered a strong market penetration of the PWM-VSI. In this paper, the impact of semiconductor device selection, converter topologies and soft-switching techniques on medium-voltage inverter system cost are investigated and discussed.
Inverse Association of Plasma Molybdenum with Metabolic Syndrome in a Chinese Adult Population: A Case-Control Study

Molybdenum has been found to be associated with metabolic disorders. However, the relationship between molybdenum and metabolic syndrome (MetS) is still unclear. A large case-control study was conducted in a Chinese population from the baseline of Ezhou-Shenzhen cohort. A total of 5356 subjects were included with 2678 MetS and 2678 controls matched by sex and age (±2 years). Medians (IQRs) of plasma molybdenum concentrations were 1.24 μg/L for MetS cases and 1.46 μg/L for controls. After adjustment for multiple covariates, the odds ratio (OR) and 95% confidence intervals (CIs) for MetS were 1.00 (reference), 0.71 (0.59–0.84), 0.56 (0.46–0.68), and 0.47 (0.39–0.58) across quartiles of plasma molybdenum, and per SD increment of log-transformed molybdenum was associated with a 23% lower risk of MetS. In the spline analysis, the risk of MetS and its components decreased steeply with increasing molybdenum and followed by a plateau when the cutoff point was observed around 2.0 μg/L. The dose-dependent relationship of molybdenum with MetS remained consistent when considering other essential elements in the Bayesian kernel machine regression (BKMR) model. In our study, higher plasma molybdenum was significantly associated with a lower risk of MetS, as well as its components, in a dose-response manner.
Topological clustering as a tool for planning water quality monitoring in water distribution networks

Topological clustering was explored as a tool for water supply utilities in preparation of monitoring and contamination contingency plans. A complex water distribution network model of Copenhagen, Denmark, was simplified by topological clustering into recognizable water movement patterns to: (1) identify steady clusters for a part of the network where an actual contamination has occurred; (2) analyze this event by the use of mesh diagrams; and (3) analyze the use of mesh diagrams as a decision support tool for planning water quality monitoring. Initially, the network model was divided into strongly and weakly connected clusters for selected time periods and mesh diagrams were used for analysing cluster connections in the Norrebro district. Here, areas of particular interest for water quality monitoring were identified by including user-information about consumption rates and consumers particular sensitive towards water quality deterioration. The analysis revealed sampling locations within steady clusters, which increased samples' comparability over time. Furthermore, the method provided a simplified overview of water movement in complex distribution networks, and could assist identification of potential contamination and affected consumers in contamination cases. Although still in development, the method shows potential for assisting utilities during planning of monitoring programs and as decision support tool during emergency contingency situations.
Murburn precepts for lactic‐acidosis, Cori cycle, and Warburg effect: Interactive dynamics of dehydrogenases, protons, and oxygen

It is unresolved why lactate is transported to the liver for further utilization within the physiological purview of Cori cycle, when muscles have more lactate dehydrogenase (LDH) than liver. We point out that the answer lies in thermodynamics/equilibriums. While the utilization of NADH for the reduction of pyruvate to lactate can be mediated via the classical mechanism, the oxidation of lactate (with/without the uphill reduction of NAD+) necessitates alternative physiological approaches. The latter pathway occurs via interactive equilibriums involving the enzyme, protons and oxygen or diffusible reactive oxygen species (DROS). Since liver has high DROS, the murburn activity at LDH would enable the cellular system to tide over the unfavorable energy barriers of the forward reaction (~476 kJ/mol; earlier miscalculated as ~26 kJ/mole). Further, the new mechanism does not necessitate any “smart decision‐making” or sophisticated control by/of proteins. The DROS‐based murburn theory explains the invariant active‐site structure of LDH isozymes and their multimeric nature. The theoretical insights, in silico evidence and analyses of literature herein also enrich our understanding of the underpinnings of “lactic acidosis” (lowering of physiological pH accompanied by lactate production), Warburg effect (increased lactate production at high pO2 by cancer cells) and approach for cancer therapy.
UV-C irradiation before or after inoculation with Colletotrichum gloeosporioides affected phytohormones and antioxidants in apple fruit (Malus domestica Borkh.)

decay caused by C. gloeosporioides (cid:133)(cid:145)(cid:143)(cid:146)(cid:131)(cid:148)(cid:135)(cid:134)(cid:3)(cid:150)(cid:145)(cid:3)(cid:24)(cid:25)(cid:486) AI due to the induction of endogenous JA accumulation and the up-regulation of PR genes. The crosstalk between JA and ethylene may also play a role in the defense mechanism against pathogen infection in apple fruit. infected with C. gloeosporioides . These results suggest that the increases in bioactive sub-(cid:149)(cid:150)(cid:131)(cid:144)(cid:133)(cid:135)(cid:149)(cid:3) induced after irradiation with UV-C. UV-C irradiation may enhance the synthesis of secondary metabolites associated with the inhibition of pathogen infection. Furthermore, our study also revealed that UV-BI increased DPPH antioxidant