Miracle-dz/UniFAR-FTUs huggingface dataset:
Application of Organisational Justice Theory to Performance Appraisal – a Study Conducted in the Service Sector Enterprises in Kerala

Purpose: Globalisation has now become a very common word. It has been the topic of discussion during the last two decades. What globalisation implies is that a country's economy synchronises with the global economy. As the result, severe competition originated in the market. The firm-to-firm competition forced the companies to enhance their productivity and efficiency. Today, PA is used as a most imperative component of HR practices. It helps to assess the performance of employees based on predetermined standards and it enables the HR department to increase the efficiency of employees as well as the organisation. Greenberg was one to apply the theory of organisational justice to Performance Appraisal (PA). Application Greenberg's theory in performance appraisal helps to ensure the system of performance appraisal is fair and just. This study was conducted in five sub-sectors of the service sector in Kerala and primary data was collected from employees. The study is used to understand the application of Greenberg theory in service sector enterprises in Kerala to know the level of justice and fairness of PAS. Methodology: The study was conducted in the service sector in Kerala. The primary data were acquired through a questionnaire. In this study, the different sectors (Financial Services, Tourism and hospitality, Media and entertainment, Telecommunications, Retail) were randomly selected. Organisations conducting a system of employee Performance Appraisal were considered in this study. A total of 543 samples were selected for the study from the five sectors. The samples were selected randomly. The questionnaire was used as a primary data collection tool. Finding: The results found that, in Kerala, different sectors follow different methods of performance appraisal techniques to their employees. The methods are different from one sector to another. And the study also found that, the employees in the service sector enterprises in Kerala were believed that the performance appraisal system is fair and just. Finally, the study revealed that the private sector PA system is more effective than the public sector. The techniques used in the private sector were more competent than public sector enterprises. Originality: This is used to conduct the application of organisational justice theory employee performance appraisal in the service sector enterprises in Kerala. Paper Type: Applied Research
CPTu-SPT correlation analyses based on pairwise data in Southwestern Taiwan

ABSTRACT Although the piezocone penetration test (CPTu) is becoming increasingly popular in site investigation, the standard penetration test (SPT) is still widely adopted in engineering practices. Additionally, a lot of empirical formulas in geotechnical engineering are based on the SPT data, rather than CPTu data. Hence, analysis of CPTu-SPT correlations is a great issue in geotechnical engineering. In this paper, CPTu-SPT correlations are analyzed based on a high-quality side-by-side CPTu-SPT database established in Southwestern Taiwan. The conventional CPT-SPT correlations are first validated with the database collected, through which the importance of formulating a new transformation model is highlighted. Then, CPTu-SPT correlations are studied using multivariate linear regression (MLR) analysis based on this database, and the best transformation model (for predicting SPT N 60-value from CPTu data) is identified by the best subset regression method. In comparison to traditional transformation models, this new model considers the pore water pressure, soil behaviour type index, and effective overburden stress explicitly; as an outcome, this new model could yield higher accuracy in mapping CPTu-SPT correlations. Finally, this new model is validated by the other set of pairwise data collected in Turkey, and the advantages of this new model over artificial neural network (ANN) models are discussed.
Pulskonturmessung im Ohr

Zusammenfassung In der CiS Forschungsinstitut für Mikrosensorik GmbH entwickelte photoplethysmographische (PPG-)Sensoren wurden spektral und geometrisch optimiert, um eine detaillierte Formanalyse von im Ohr gemessenen Pulswellen zu ermöglichen. Verschiedene Auswerteverfahren der Pulskontur wurden bezüglich ihrer Eignung für Pulswellen-Laufzeitmessung untersucht. Der Vergleich der im-Ohr-PPG-Pulsform mit der an einer Manschette zeitsynchron aufgenommenen suprasystolischen Druckwelle führte zu einem Modell für die Übertragung der Druckwelle in das PPG. Mit der daraus ableitbaren Rückrechnung des PPG in ein Abbild der peripheren Blutdruckwelle ergeben sich neue Möglichkeiten der Langzeit-Überwachung des Herz-Kreislauf-Zustandes.
Flavonoids Target Human Herpesviruses That Infect the Nervous System: Mechanisms of Action and Therapeutic Insights

Human herpesviruses (HHVs) are large DNA viruses with highly infectious characteristics. HHVs can induce lytic and latent infections in their host, and most of these viruses are neurotropic, with the capacity to generate severe and chronic neurological diseases of the peripheral nervous system (PNS) and central nervous system (CNS). Treatment of HHV infections based on strategies that include natural products-derived drugs is one of the most rapidly developing fields of modern medicine. Therefore, in this paper, we lend insights into the recent advances that have been achieved during the past five years in utilizing flavonoids as promising natural drugs for the treatment of HHVs infections of the nervous system such as alpha-herpesviruses (herpes simplex virus type 1, type 2, and varicella-zoster virus), beta-herpesviruses (human cytomegalovirus), and gamma-herpesviruses (Epstein–Barr virus and Kaposi sarcoma-associated herpesvirus). The neurological complications associated with infections induced by the reviewed herpesviruses are emphasized. Additionally, this work covers all possible mechanisms and pathways by which flavonoids induce promising therapeutic actions against the above-mentioned herpesviruses.
Localization of coal mine rescue robots based on multi-sensor fusion

This paper investigates the multi-sensor fusion positioning problem coal mine rescue robots to deal with the complex catastrophic underground environment subject to poor illumination and slippery road. A multi-sensor fusion positioning system is designed by combining lidar, IMU, and wheel encoder and a multi-sensor fusion positioning method is proposed based on extended Kalman filter with fuzzy confidence. By the proposed method, the wheel slip can be described and used to regulate the confidence level of the wheel odometry information in the fusion positioning system in real-time, and change the covariance matrix dynamically to improve the adaptability of the system to the subterranean environment and enhance the positioning accuracy. The experimental results show that the system is suitable for underground positioning, and the proposed positioning algorithm is of higher accuracy than the conventional single sensor positioning methods and the extended Kalman filter fusion positioning methods.
Polymerase Epsilon-Associated Ultramutagenesis in Cancer

Simple Summary DNA polymerase epsilon is implicated to play a major role in DNA synthesis of the leading strand. In some cancer types, especially colorectal and endometrial cancers, polymerase epsilon is mutated at several hotspots, causing large amounts of mutations, termed ultramutation. The aim of this article is to describe the characteristics of polymerase epsilon mutations including their mutation sites and signatures, elucidate the underlying mechanisms of its ultramutagenesis, discuss its good prognosis and favorable responses to immunotherapies, and speculate on possible strategies to improve treatment of ultramutated cancers. Abstract With advances in next generation sequencing (NGS) technologies, efforts have been made to develop personalized medicine, targeting the specific genetic makeup of an individual. Somatic or germline DNA Polymerase epsilon (PolE) mutations cause ultramutated (>100 mutations/Mb) cancer. In contrast to mismatch repair-deficient hypermutated (>10 mutations/Mb) cancer, PolE-associated cancer is primarily microsatellite stable (MSS) In this article, we provide a comprehensive review of this PolE-associated ultramutated tumor. We describe its molecular characteristics, including the mutation sites and mutation signature of this type of tumor and the mechanism of its ultramutagenesis. We discuss its good clinical prognosis and elucidate the mechanism for enhanced immunogenicity with a high tumor mutation burden, increased neoantigen load, and enriched tumor-infiltrating lymphocytes. We also provide the rationale for immune checkpoint inhibitors in PolE-mutated tumors.
Comunicarea în evaluarea programelor și politicilor publice (Communication for the Evaluation of Public Programmes and Policies)

Romanian Abstract: Comunicarea rezultatelor evaluării este esențială pentru un proiect sau program, intrucât poate ridica sau reduce valoarea acestuia in fața partenerilor și a publicului larg. Rolul comunicării in acest proces este de a construi o relație intre actorii implicați, generatoare de schimburi de informații de calitate, care să contribuie la crearea unui mediu cooperant și participativ, bazat pe incredere reciprocă și pe respect. Aceasta va ajuta la obținerea celor mai bune rezultate in procesul de evaluare și la identificarea celor mai bune soluții pentru imbunătățirea programului sau politicii analizate.English Abstract: Communicating the evaluation results is essential for a project or programme, because it can raise or reduce the project value in front of its partners and of the general public. During this process, the communication has an important function: to build a relationship between the actors involved, which will generate valuable information exchanges, creating a cooperative and participative environment. This will help in getting the best results in the evaluation process and identifying the best solutions for the improvement of the programme or policy.
Improving Local Trajectory Optimization by Enhanced Initialization and Global Guidance

Trajectory optimization is a promising method for planning trajectories of robotic manipulators. With the increasing success of collaborative robots in dynamic environments, the demand for online planning methods grows and offers new opportunities as well as challenges for trajectory optimization. Special requirements in terms of real-time capabilities are one of the greatest difficulties. Optimizing a short planning horizon instead of an entire trajectory is one approach to reduce computation time, which nonetheless separates the optimality of local and global solutions. This contribution introduces, on the one hand, Extended Initialization as a new approach that reduces the risk of local minima and aims at improving the quality of the global trajectory. On the other hand, the particularly critical cases in which local solutions lead to standstills are mitigated by globally guiding local solutions. The evaluation performs four experiments with comparisons to Stochastic Trajectory Optimization for Motion Planning (STOMP) or Probabilistic Roadmap Method (PRM*) and demonstrates the effectiveness of both approaches.
Rape myth acceptance is lower and predicts harsher evaluations of rape among impacted people

Public reactions to rape are often distorted by the acceptance of so-called rape myths. The goal of our research was to examine how rape myth acceptance (RMA) is connected to the evaluation of rape cases among survivors, unimpacted people, and those impacted by rape through a close relation, who can potentially be important allies of survivors in bringing about social change. We tested these connections in three online survey studies. In Study 1 (N = 758) we found that those impacted by rape personally or through a close relation accepted rape myths less. In Study 2, using a nationally representative sample in Hungary (N = 1007), we tested whether RMA predicted uncertain rape cases more strongly than certain (i.e., stereotypical) ones, considering that a stereotypical rape scenario is condemned by most members of society, but not all rape is labeled as such. We found that RMA predicted the evaluation of both rape scenarios, but the prediction was stronger when rape was uncertain. In Study 3 (N = 384), in a pre-registered study we examined how RMA predicted the evaluation of rape cases amongst people with different previous experiences (impacted/unimpacted). We found that unimpacted people accepted rape myths more, blamed the victim more and labeled the case less as rape when the case was uncertain. These findings suggest that rape myth acceptance functions as cognitive schema and that rape impacted people could have a key role not only in the life of survivors but as allies for social change as well.
Effects of exogenous salicylic acid and abscisic acid on growth, photosynthesis and antioxidant system of rice

The key function of plant growth regulators is to adjust the growth and development of plants to adapt to the changing environment, which plays a vital role in the growth and yield of crops. This study was aimed to evaluate the ability of foliar application of salicylic acid (SA) and abscisic acid (ABA) to regulate rice (Oryza sativa L.) growth quality at seedling stage and reproductive stage. The two rice cultivars Wanshengyoutianhong-4 (W4) and Huanghuazhan (HZ) were sprayed foliar with SA (100 mg L-1) and ABA (4 mg L-1) at two-leaf stage, and their effects on morphological growth, physiological characteristics, malondialdehyde (MDA), osmotic substances, protective enzyme activities, photosynthesis and yield components were studied. Results indicated that SA and ABA significantly increased morphological growth, osmotic substances, antioxidant enzyme activities; MDA content dropped significantly (p < 0.05) in W4. While the two regulators inhibited morphological growth and physiological characteristics in HZ. Additionally, net photosynthesis, stomatal conductance, transpiration rate, water use efficiency and apparent mesophyll conductance were improved in both of rice cultivars at heading stage as well as grain weight. In conclusion, foliar spray of SA and ABA enhanced plant growth, induced an increase in protective enzyme activities and reduced the oxidative damage of the hybrid rice cultivar but not of the conventional rice cultivar at seedling stage. Meanwhile, photosynthetic parameters and grain weight were slightly enhanced at reproductive stage. These results served as a theoretical basis and technical support for the chemical regulation and cultivation practices of rice.
Automatic Information Extraction in the Third-Generation Semiconductor Materials Domain Based on DKNet and MANet

The third-generation semiconductor materials (TGSMs) is a frontier scientific domain, where researchers need to consult extensive literature for the entity information on materials, devices, preparation methods, and experimental performances, and sort out the complex relations between them. However, the explosion of relevant papers has far exceeded researchers’ reading ability. In this article, the TGSM-field automatic information extraction is conducted based on entity recognition (ER) and relation extraction (RE) techniques. First, the corpora used for ER and RE in this field are created. Second, aiming at the complexity of the entities, a neural network using domain knowledge (DKNet) is proposed to improve ER performance. It uses the keyword sequence of each entity type as prior knowledge, adds a dedicated embedding to encode entity categories, then combines prior knowledge and encoded vectors with the context through a gated information fusion module to assist recognition. As for the indicative word dependence problem of entity relations, a multi-aspect attention-based network model (MANet) is proposed to enhance the attention to relation-indicative words, thereby improving the RE performance. Finally, F1 scores of 74.5 and 85.9 were achieved on the created ER and RE test sets, outperforming other advanced models by $3.4~\sim ~10.1$ , which is the best performance of the TGSM-field automatic information extraction.
Wafer map defect recognition with few shot learning based on hybrid self-attention mechanism and prototype network

Semiconductor manufacturing is a very complex dynamic manufacturing process. Wafer manufacturing is the most critical part of it. Abnormalities in any process in wafer production may cause wafer defects. Accurately identifying various defect patterns on the wafer surface can help find and adjust abnormal factors in the online manufacturing process and improve the yield of integrated circuit production. Aiming at the very small number of wafer defect patterns that appear in the wafer manufacturing process, this paper proposes a small sample wafer defect pattern classification method based on a hybrid self-attention mechanism and a prototype network. This method introduces a hybrid self-attention module into the feature embedding network that helps to automatically learn the global dependence of channels and positions in the wafer map to obtain more discriminative features. The metric classifier is used for classification to realize the pattern recognition of wafer defects in small samples. A large number of experiments were conducted on the WM-811K data set and the MixedWM38 data set. The recognition accuracy of this method in the 3-way 1-shot, 3-way 5-shot, 5-way 1-shot and 5-way 5-shot tasks achieved average classification accuracy rates of 89.99%, 94.96%, 85.77%, and 92.32%, respectively. The experimental results show that compared with the traditional deep learning method, the method in this paper can learn new defect pattern features and realize automatic classification only through a small number of wafer samples.
Is Maintaining Thyroid-Stimulating Hormone Effective in Patients Undergoing Thyroid Lobectomy for Low-Risk Differentiated Thyroid Cancer? A Systematic Review and Meta-Analysis

Simple Summary In order to reduce the recurrence rate after surgical treatment of differentiated thyroid cancer (DTC), suppression of thyroid-stimulating hormone (TSH) or maintenance of a certain level after surgery are important. However, the effectiveness of TSH maintenance in the mid to lower reference range (0.5–2 mU/L) in patients undergoing thyroid lobectomy for low-risk DTC is uncertain. In this systematic review and meta-analysis, we compared and analyzed the recurrence rate according to whether TSH maintenance was performed in patients who underwent thyroid lobectomy for low-risk DTC. There was no difference in the recurrence rate with or without TSH control. Therefore, the recommendation to maintain TSH to reduce the recurrence rate after thyroid lobectomy is still controversial. Abstract There is no clear evidence that post-operative maintenance of thyroid-stimulating hormone (TSH) in the mid to lower reference range (0.5–2 mU/L) improves prognosis in patients undergoing thyroid lobectomy for low-risk differentiated thyroid cancer (DTC). The purpose of this systematic review and meta-analysis was to compare and analyze the recurrence rate according to whether the serum TSH level was maintained below 2 mU/L in patients who underwent thyroid lobectomy for low-risk DTC. Clinical data and outcomes were collected from MEDLINE, Embase, and the Cochrane Database of Systematic Reviews. The inclusion criteria were related studies on TSH maintenance or serum TSH concentration after surgery for DTC. Seven observational studies with a total of 3974 patients were included in this study. In the patients who received TSH maintenance less than 2 mU/L, the recurrence rate during the follow-up period was 2.3%. A subgroup analysis of five studies showed that the odds ratio for recurrence in patients who received TSH maintenance was 1.45 (p-value = 0.45) compared to patients who did not receive TSH maintenance. In conclusion, the evidence for the effectiveness of post-operative TSH maintenance less than 2 mU/L in patients undergoing thyroid lobectomy for low-risk DTC is insufficient.
Down Regulation in Glutathione S-Transferase Stimulate Oxidative Stress and Genetic Susceptibility of Human Breast Cancer

Glutathione S-Transferase is an enzyme that catalyzed the formation of thio-ether conjugates between the endogenous tripeptide glutathione and xenobiotic compounds. Imbalance of glutathione level is observed in a variety of disease including breast cancer. In the present study we observed the alteration in the glutathione level and variation in glutathione S-transferase enzyme supergene family to influence susceptibility to breast cancer disease. Our study include 50 breast cancer tissues sample along with 25 ANCT control. The experiments were performed through high performance liquid chromatography to determine the endogenous glutathione level and multiplex PCR was used to determine GSTM1 & GSTT1 genotypes. The relationship between breast cancer and disease progression and histological grade were estimated by one way ANOVA and descriptive statisctics followed by spearman correlation {S.D±SEM, 95% CI (P<0.05)}. The study show decreased level of glutathione (GSHt P<0.05, GSH, GSSG P>0.05) in breast cancer tissue sample when compared to control, while no significance difference was occurred in GST (P>0.05) concentration when compared to control. In addition significance difference was observed when correlated histological grades {(grade II P<0.05) gradeII & III P>0.05)} with control subjects. We therefore, also investigated the role of GST genotypes to associate the role of this genotype in breast cancer. Genotyping study of GST show that the GSTM1 (P>0.05) null genotype was significantly associated with breast cancer and we found no association with breast cancer and GSTT1 (P<0.05) null genotype. In conclusion our study suggest that the dysregulation of glutathione level were associated with breast cancer and GSTM1 null genotype could be a useful marker for breast cancer prognosis.
Graph Attention based Point Cloud Registration

Point cloud registration is a fundamental but important technique in robotics and computer vision, such as 3D reconstruction, simultaneous localization and mapping (SLAM). The classical methods used hand-craft features extracted from each point cloud to estimate the rigid transformation between point clouds with iterative closest points (ICP) or its variants. Recently, deep learning has been widely used in object detection, segmentation and registration, especially the well-known work, PointNet, changed how we think about the representation of point clouds. However, the local information is ignored in PointNet as many works pointed out. In this paper, we advise to use graph attention to aggregate local features and a kind of cross attention method for point cloud registration. Firstly, we use a mini-ConvNet to extract point-wise features for sampled points and their neighbors. Then graph attention is applied to aggregate the local information from neighbor points to center points. We consider that previous works which directly estimate the transformation using the features from two point clouds ignore some relationship between the point clouds. Instead, we propose to explore the relation with a kind of cross attention. We perform extensive experiments to validate the effectiveness of our method.