Early Stages Of Process Research Articles

Rumor detection methodology based on sentiment analysis and the transformer model with decision-level fusion

The use of transformer models in natural language processing (NLP) has gained significant attention in recent years due to their exceptional performance in various language tasks. This paper explores the application of transformer models in rumor detection, the relevant research on rumor detection, the use of transformer models, and the techniques used to boost the models performance. Ultimately, the purpose of this paper is to provide insight into the potential of transformer models in detecting rumors on social media. Unlike other rumor-detecting models, the author adds a sentiment analysis model as a supplement to rumor detection. Also, to address the issue of insufficient information in early-stage comments on rumors, this paper proposes a decision-level fusion method before the output layer, which effectively utilizes information from different sources and minimizes the negative impact of insufficient data sources. The early-stage rumor detection accuracy of the model is greatly enhanced by this method, therefore, the articles main contributions can be regarded as follows: First, this paper proposes a combination of an aspect level text sentiment analysis method according to syntactic features, gated recurrent units, and a self-attention mechanism. Experimental findings demonstrate that, compared to the original model without taking the sentiment analysis method into account, the proposed network model has advantages in accuracy and Macro F1 evaluation indexes. Second, a cross-text rumor-detecting method based on Decision-level fusion is proposed. Its advantage is that when the cross-text data source is incomplete and a certain text is missing, another text can be used to continue the analysis. Experimental findings show the effectiveness of this method in improving the accuracy of emotion recognition by integrating data from different modes. Third, a comparison is conducted between the performance of the Transformer-sentiment model and other related models, Text-CNN, Bi-LSTM, etc. The result shows that this integrated Transformer-sentiment model can not only solve the rumor detection tasks at higher accuracy, but can also overcome the shortcomings of the lack of datasets, which means that the model is more robust, and is able to detect rumors at the early stage of the rumor spreading process.

Impact of automatic acquisition of key clinical information on the accuracy of electrocardiogram interpretation: a cross-sectional study

BackgroundThe accuracy of electrocardiogram (ECG) interpretation by doctors are affected by the available clinical information. However, having a complete set of clinical details before making a diagnosis is very difficult in the clinical setting especially in the early stages of the admission process. Therefore, we developed an artificial intelligence-assisted ECG diagnostic system (AI-ECG) using natural language processing to provide screened key clinical information during ECG interpretation.MethodsDoctors with varying levels of training were asked to make diagnoses from 50 ECGs using a common ECG diagnosis system that does not contain clinical information. After a two-week-blanking period, the same set of ECGs was reinterpreted by the same doctors with AI-ECG containing clinical information. Two cardiologists independently provided diagnostic criteria for 50 ECGs, and discrepancies were resolved by consensus or, if necessary, by a third cardiologist. The accuracy of ECG interpretation was assessed, with each response scored as correct/partially correct = 1 or incorrect = 0.ResultsThe mean accuracy of ECG interpretation was 30.2% and 36.2% with the common ECG system and AI-ECG system, respectively. Compared to the unaided ECG system, the accuracy of interpretation was significantly improved with the AI-ECG system (P for paired t-test = 0.002). For senior doctors, no improvement was found in ECG interpretation accuracy, while an AI-ECG system was associated with 27% higher mean scores (24.3 ± 9.4% vs. 30.9 ± 10.6%, P = 0.005) for junior doctors.ConclusionIntelligently screened key clinical information could improve the accuracy of ECG interpretation by doctors, especially for junior doctors.

The relation between naturalistic use of psychedelics and perception of emotional stimuli: An event-related potential study comparing non-users and experienced users of classic psychedelics.

Previous research has suggested that controlled administration of psychedelic substances can modulate emotional reactivity, enhancing positive and diminishing negative emotions. However, it is unclear whether similar effects are associated with using psychedelics in less-controlled naturalistic environments. This cross-sectional study investigated the neural markers associated with the perception of emotional stimuli in individuals with extensive experience of naturalistic psychedelic use (15 or more lifetime experiences), comparing them to non-users. Electroencephalography (EEG) signals were recorded from two groups: experienced psychedelics users (N = 56) and non-users (N = 55). Participants were presented with facial images depicting neutral or emotional expressions (anger, sadness, and happiness). Event-related potential (ERP) components were analyzed as indices of emotional reactivity. Psychedelic users were characterized by significantly lower amplitudes of the N200 component in response to fearful faces, in comparison to non-users. In addition, interaction effects between Group and Emotional expression were observed on N170 and N200 amplitudes, indicating group differences in the processing of fearful faces. However, no significant between-group differences emerged in the analysis of later ERP components associated with attention and cognitive processes (P200 and P300). The results suggest that naturalistic use of psychedelics may be linked to reduced reactivity to emotionally negative stimuli at the early and automatic processing stages. Our study contributes to a better understanding of the effects related to using psychedelics in naturalistic contexts.

Defective kernel 58 encodes an Rrp15p domain-containing protein essential to ribosome biogenesis and seed development in maize.

Ribosome biogenesis is a highly dynamic and orchestrated process facilitated by hundreds of ribosomal biogenesis factors and small nucleolar RNAs. While many of the advances are derived from studies in yeast, ribosome biogenesis remains largely unknown in plants despite its importance to plant growth and development. Through characterizing the maize (Zea mays) defective kernel and embryo-lethal mutant dek58, we show that DEK58 encodes an Rrp15p domain-containing protein with 15.3% identity to yeast Rrp15. Over-expression of DEK58 rescues the mutant phenotype. DEK58 is localized in the nucleolus. Ribosome profiling and RNA gel blot analyses show that the absence of DEK58 reduces ribosome assembly and impedes pre-rRNA processing, accompanied by the accumulation of nearly all the pre-rRNA processing intermediates and the production of an aberrant processing product P-25S*. DEK58 interacts with ZmSSF1, a maize homolog of the yeast Ssf1 in the 60S processome. DEK58 and ZmSSF1 interact with ZmCK2α, a putative component of the yeast UTP-C complex involved in the small ribosomal subunit processome. These results demonstrate that DEK58 is essential to seed development in maize. It functions in the early stage of pre-rRNA processing in ribosome biogenesis, possibly through interacting with ZmSSF1 and ZmCK2α in maize.

Tau conformational changes in aging‐related tau astrogliopathy.

AbstractBackgroundThe presence of aging‐related tau astrogliopathy (ARTAG) is highly frequent, but poorly characterized in aging brain and neurodegeneration. Over the abnormal tau accumulation processes, tau protein undergoes pathological modifications and the sequency of these pathological events can be associated with different levels of tau aggregation.MethodTo evaluate the frequency of ARTAG in a large population‐based study, we analyzed brain sections immunostained with phosphor tau (AT8) of 1151 individuals with previous neuropathological evaluation. Further, to investigate early stages of tau protein aggregation in ARTAG, we performed additional immunohistochemistry in the amygdala of 32 cases with ARTAG pathology using the following tau antibodies: AT100 and Tau‐C3.ResultARTAG was frequently observed in cognitively normal individuals independent of concomitant neurodegenerative disease. Higher burden of Alzheimer‐type pathology was observed in ARTAG compared to non‐ARTAG. Also, presence of more than one pathology (mixed pathology) was higher in ARTAG compared to non‐ARTAG (p<0.001). Additionally, AT100 immunoreactive ARTAG was found in overall cases, while Tau‐C3 immunoreactive ARTAG was not observed in 12 cases (36%), showing different mature stage for ARTAG compared to neurofibrillary tangles.ConclusionDifferent immunological markers can be found in ARTAG and Alzheimer’s neurofibrillary pathology in early stages of tau pathological processing, suggesting different levels of abnormal tau aggregates among cases with ARTAG pathology.

Appressoria-Producing Sordariomycetes Taxa Associated with Jasminum Species.

Appressoria are specialized structures formed by certain phytopathogenic fungi during the early stages of the infection process. Over the years, significant advancements have been made in understanding the formation, types, and functions of appressoria. Besides being formed primarily by fungal pathogens, many studies have reported their occurrence in other life modes such as endophytes, epiphytes, and saprobes. In this study, we observed the formation of appressoria in fungal genera that have been found associated with leaf spots and, interestingly, by a saprobic species. We used morphological descriptions and illustrations, molecular phylogeny, coalescent-based Poisson tree processes (PTP) model, inter- and intra-species genetic distances based on their respective DNA markers, and Genealogical Concordance Phylogenetic Species Recognition Analysis (GCPSR) to establish a new species (Pseudoplagiostoma jasmini), a Ciliochorella sp., and a new host record (Coniella malaysiana). The Ciliochorella sp. is reported as a saprobe, while Pseudoplagiostoma jasmini and Coniella malaysiana were found to be associated with leaf spots of Jasminum species. All three taxa produce appressoria, and this is the first study that reports the formation of appressoria by a Ciliochorella sp. and a Pseudoplagiostoma sp.

Trogocytosis-Resistant CAR T Cells Exhibit Increased Persistence and Prevent Antigen Escape

Chimeric Antigen Receptor (CAR) T cell therapy is a highly effective treatment for cancer patients in which T cells are genetically modified to express a CAR targeting an antigen expressed on the surface of cancer cells. While CAR T cells have shown remarkable efficacy, many patients receiving CAR T cell therapy relapse within five years of treatment. It has recently been shown that tumor cells can escape killing by CAR T cells using a mechanism called trogocytosis. CAR-mediated trogocytosis (CMT) involves the transfer of cell surface proteins from tumor cells to CAR T cells. Antigen transfer by CMT results in antigen-negative tumor cells and reduced CAR T cell persistence due to increased CAR T cell exhaustion and fratricide. To date, the molecular processes causing CMT remain poorly understood and there are currently no approaches to therapeutically target CMT. To track CMT in real-time, we first developed a custom luciferase complementation assay with a detection limit of approximately 100 CAR T cells displaying the target antigen (CompLuc). Using this assay, we found that CMT is effector-target ratio and time-dependent and can be modulated by inhibiting actin polymerization, a process essential for key T cell functions including vesicle formation, protein transport, and target cell killing. To develop a universal approach to inhibit CMT in CAR T cells without altering tumor cell killing, we investigated the effect of inhibiting adhesion, endocytosis, vesicle formation, and proteolytic degradation using various small-molecule inhibitors. We found that inhibition of the cysteine protease Cathepsin B with the small molecule inhibitor Ca-074-Me significantly reduced CMT as determined by CompLuc assay and flow cytometry. Performing a luciferase-based cytotoxicity assay, we found that Cathepsin B inhibition does not affect tumor cell killing. Based on these data, we hypothesized that Cathepsin B inhibition could be a potential therapeutic approach to limit CMT. Cathepsin B activity in human cells is regulated by the human proteins Cystatin A and Cystatin B. Structural data of Cathepsin B in complex with Ca-074-Me or Cystatin A show that both molecules appear to sterically block access of substrates to the active site cysteine of Cathepsin B. We therefore explored if overexpression of cystatins in CAR T cells could be an efficient approach to inhibit CMT. We found that overexpression of Cystatin A significantly reduced Cathepsin B activity in CAR T cells and limited transfer of tumor antigen to CAR T cells. We also observed that cystatin overexpression reduced loss of antigen from the tumor cell surface, indicating that Cathepsin B inhibition blocks CMT at an early stage of the trogocytic process. Importantly, Cystatin A overexpression did not alter CAR T cell expansion, tumor cell killing, or CAR T cell phenotype, indicating that this approach selectively inhibits CMT and that key CAR T cell functions remain intact. Cystatin overexpression also led to significantly increased tumor-specific CAR T cell numbers (78% of non-targeting CAR T cells) compared to wild-type CAR T cells (61% of non-targeting CAR T cells, p = 0.0298) after 24 h exposure to tumor cells, indicating that selective inhibition of CMT prevents CAR T cell fratricide and/or exhaustion. To further reduce presence of antigen on CAR T cells following CMT, we next developed a system to actively degrade the trogocytosed protein in CAR T cells. Specifically, we developed a fusion protein combining the SH2 domain of the Src kinase Lyn, which binds with high affinity to the intracellular domain of CD19, with the von Hippel-Lindau E3 ubiquitin ligase. We show that expression of this fusion protein within CAR T cells rapidly targets trogocytosed CD19 for degradation and eliminates its presence on the surface of CAR T cells. Trogocytosed antigen degradation also increased CAR T cell survival at the end of in vitro co-culture, indicating reduced CAR T cell fratricide and/or exhaustion. Taken together, we provide the first preclinical proof-of-concept that, using a fully human genetic engineering approach, CMT can be targeted without compromising essential CAR T cell functions. This represents a promising approach to improve CAR T cell efficacy and limit the occurrence of relapse in patients receiving CAR T cell therapy.

Investigation of the thermal exchange mechanism of PCM melting process in an LHTES with elliptic tube configurations inside a cylindrical shell

This study presents a comprehensive 2D numerical investigation into the heat transfer mechanisms and melting time estimation for a phase change material melting process in latent heat thermal energy storage systems. The energy storage system of interest employs an elliptic tube configuration within a cylindrical shell. This study primarily aims to decipher the impact of spatial arrangement and its geometrical intricacies on melting time and the associated heat transfer mechanisms. First, this study examines the transition in the dominant heat transfer mechanisms, from conduction to natural convection, throughout the progression of the melting process. The examination is facilitated using the enthalpy porosity method, which can articulate an additional momentum term by leveraging the porosity at the melting interface and the local liquid fraction. Conduction dominance characterizes the early stages of the melting process; however, a transition toward a complex interplay of natural convection and conduction is observed as the process evolves. When the distance between the heat source and the outer covering is changed from a measure of 0.95 to 0.7, the time it takes for phase change material to melt increases by 73.2%. Additionally, when the shape of a certain heat transfer fluid carrier cylinder and the space between them in angles (from 1/8 to 8 and from 30° to 150°) are adjusted, the melting time changes by 31.1% and 38.9% respectively. In addition to the numerical analysis, this study introduces an innovative predictive model based on artificial neural networks to forecast the melting time of the phase change material in the energy storage system. This predictive model is trained and validated using the data derived from the numerical study and shows good accuracy in predicting the melting time, which is a critical factor for the efficiency and performance of systems.

Smart PSS modelling language for value offer prototyping: A design case study in the field of heating appliance offers

The recent convergence between two industrial transitions towards digitalization on the one side and servitization on the other side led to the new business strategies of digital servitization and smart PSS delivery. While inheriting from the previous scientific literature on PSS, because of the multiple impacts of digitalization in the overall system, the processes of ensuring the design and engineering of smart PSS solutions poses new challenges. This research addresses the specific needs to develop conceptual prototypes of smart PSS value offers, at early stages of the design process. The paper presents the development and experimentation of a modelling language and its associated modelling toolkit (sPS²Modeller). The application case study addresses the design of a smart PSS in the field of heating appliances, developed in collaboration with the company elm.leblanc, Bosch Group – France.

Semi-Supervised Classification of Malware Families Under Extreme Class Imbalance via Hierarchical Non-Negative Matrix Factorization with Automatic Model Selection

Identification of the family to which a malware specimen belongs is essential in understanding the behavior of the malware and developing mitigation strategies. Solutions proposed by prior work, however, are often not practicable due to the lack of realistic evaluation factors. These factors include learning under class imbalance, the ability to identify new malware, and the cost of production-quality labeled data. In practice, deployed models face prominent, rare, and new malware families. At the same time, obtaining a large quantity of up-to-date labeled malware for training a model can be expensive. In this article, we address these problems and propose a novel hierarchical semi-supervised algorithm, which we call the HNMFk Classifier , that can be used in the early stages of the malware family labeling process. Our method is based on non-negative matrix factorization with automatic model selection, that is, with an estimation of the number of clusters. With HNMFk Classifier , we exploit the hierarchical structure of the malware data together with a semi-supervised setup, which enables us to classify malware families under conditions of extreme class imbalance. Our solution can perform abstaining predictions, or rejection option, which yields promising results in the identification of novel malware families and helps with maintaining the performance of the model when a low quantity of labeled data is used. We perform bulk classification of nearly 2,900 both rare and prominent malware families, through static analysis, using nearly 388,000 samples from the EMBER-2018 corpus. In our experiments, we surpass both supervised and semi-supervised baseline models with an F1 score of 0.80.

Desulfurization Behavior of FeNi-Based Expansion Alloy Melt Using CaO-SiO2-MgO-Al2O3-CaF2 Slag

The effects of slag components on the sulfur distribution ratio {(wt.%S)/[wt.%S]} were analyzed using thermodynamic calculations. On this basis, the effects of the slag with different binary basicities (wt.% CaO/wt.% SiO2 = 3.0, 5.0, 7.0, 9.0 and 11.0) and Al2O3 contents (wt.% Al2O3 = 12, 16, 20 and 24) on the desulfurization behavior were investigated. The results show that the binary basicity and Al2O3 content were the main factors that affected the desulfurization. And an increase in the binary basicity and a decrease in the content of Al2O3, increase the sulfide capacity of the slag. In the early stage of the smelting process, the desulfurization process was limited due to the high content of oxides, such as FeO and MnO in the slag, and the sulfur content in the alloy melt reached 35 ppm. After the final deoxidation of the Si-Ca alloy, the desulfurization rate was significantly increased, and the maximum desulfurization rate reached 44.12%. During the ladle standing, the sulfur content in the alloy melt changed little because of the limitation of kinetics. The rate-limiting step of the desulfurization process was the diffusion of sulfur in the alloy melt.

An eye on semantics: a study on the influence of concreteness and predictability on early fixation durations

ABSTRACT We used eye-tracking during natural reading to study how semantic control and representation mechanisms interact for the successful comprehension of sentences, by manipulating sentence context and single-word meaning. Specifically, we examined whether a word’s semantic characteristic (concreteness) affects first fixation and gaze durations (FFDs and GDs) and whether it interacts with the predictability of a word. We used a linear mixed effects model including several possible psycholinguistic covariates. We found a small but reliable main effect of concreteness and replicated a predictability effect on FFDs, but we found no interaction between the two. The results parallel previous findings of additive effects of predictability (context) and frequency (lexical level) in fixation times. Our findings suggest that the semantics of a word and the context created by the preceding words additively influence early stages of word processing in natural sentence reading.

Flexibility; a critical concern in concept development in the early stages of architectural design process (case study: universities in Tehran)

Flexibility; a critical concern in concept development in the early stages of architectural design process (case study: universities in Tehran)

Requirements, Objectives, Both, or Neither: How to Formulate Complex Design Problems for Innovation Contests

Abstract Technical organizations increasingly rely on innovation contests to find novel ideas for designing complex systems. These activities involve outsiders in the early stages of the design process, leading to ground-breaking designs that often surpass expectations. Here, the contest’s rules document plays a crucial role: this design artifact communicates the organization’s problem and the desired system performance to the participants—significantly impacting the resulting solutions. However, the contest’s nature amplifies the challenges of communicating complex design problems across boundaries. Existing strategies for formulating—i.e., requirement and objective allocation—might not suit this context. We developed an inductive model of their formulation process based on a multiyear field study of five complex innovation contests. We found that a formulation team (or “seeker”) balanced the need to communicate their problem in detail with the risk of excluding valuable participants. Here, they chose among three approaches—incentivize, impose, or subsume—depending on their knowledge of potential solutions and the participants’ capabilities. Notably, the seeker formulated more granularly than the literature describes, employing multiple approaches within each rules document. These findings shed light on a poorly understood aspect of innovation contests, shed new light on a longstanding debate in the engineering design literature, and guide practitioners’ formulation processes.

Magnetic resonance imaging in assessing the staging of intracerebral hemorrhages in children

The purpose of the study was to evaluate the possibilities of MRI in determining the stage of hemorrhagic stroke (HS) depending on structural and perifocal changes in children.Materials and methods. The study included 46 patients (including 19 boys and 27 girls) aged from the 29th day of life to 18 years, with a clinical picture of cerebrovascular accident and the presence of HS in the brain substance (BS) during an MRI study. For statistical analysis, patients were divided into two groups: group 1 – patients examined in the first 48 hours from the onset of neurological symptoms (21 people), group 2 – after 48 hours (26 people). Comparison in two groups was carried out according to MR signs: the presence of perifocal cytotoxic edema, the presence of perifocal hemorrhagic impregnation, the presence of a cytoplasmic rim. Intergroup comparisons on a qualitative basis were carried out using Fisher's exact test.Results. As a result of the study, differential diagnostic criteria for the stages of HS in children were determined by analyzing the MRI semiotics of hematoma in combination with the symptom complex of perifocal changes (CPC) in the form of perifocal cytotoxic edema, perifocal hemorrhagic impregnation and cytoplasmic rim. Statistically significant differences in the frequency of occurrence of signs of perifocal cytotoxic edema and perifocal hemorrhagic impregnation in the groups were found. The presence of perifocal cytotoxic edema was statistically significant (p = 0.027) more common in group 1 (47% (n = 10), 95% CI 26–69) than in group 2 (16% (n = 4), 95% CI 5–36). The presence of perifocal hemorrhagic soaking was statistically significantly (p = 0.003) more common in group 1 (81% (n = 17), 95% CI 57–93) than in group 2 (36% (n = 9), 95% CI 18–57). In addition, a statistically significant (p = 0.005) difference was found in the incidence of CPC, which was observed in group 1 (28% (n = 6), CI 12–52) and was not observed in group 2 (0%, (n = 0), 95% CI 0–17).Conclusions. The use of T2, T1, FLAIR, SWI and DWI modes (b = 1000) in combination with ADC in the protocol of MRI examination of children is mandatory, and only a comparison of the characteristics of the MR signal from a hematoma in combination with an analysis of perifocal changes allows us to differentiate the stage of hemorrhage. HS in the acute and early subacute stages has a similar MRI semiotics, therefore, it is necessary to assess the complex of perifocal changes, which allows to differentiate these stages, as it is determined in patients examined in the first 48 hours (p < 0.05) and is not observed after two days. SWI analysis makes it possible to differentiate the late subacute stage of hematoma from chronic due to different characteristics of the MR signal, and also allows you to establish the presence of perifocal hemorrhagic impregnation, which contributes to the differential diagnosis of hemorrhage in the early stages of the pathological process.

The Spatial Arrangement of The Electric Field in the Needle-Plate Electrospinning

<p class="IJASEITAbtract">The electric field distribution of the Neddle-Plate (NP) electrospinning set up has reported due to the simple classical electrodynamics solutions. The charge is assumed to distribute uniformly in the needle (nozzle) and the collector (plate). The electric field has an influence only in the early stage of the electrospinning process. The electric field and the viscosity of the jet fluid have caused the bending of the straight jet. The high viscosity of the fluid can preserve the straight jet length much longer. The electric field gives the initial angular momentum of the jet due to the whipping motion of the jet. For the area away from the nozzle, the electric does not influence the whipping motion. Then the whipping motion solely due to the influence from the charge repulsion of the jet fluid and the evaporation of the solvent.</p>

Self-Paced Co-Training of Graph Neural Networks for Semi-Supervised Node Classification.

Graph neural networks (GNNs) have demonstrated great success in many graph data-based applications. The impressive behavior of GNNs typically relies on the availability of a sufficient amount of labeled data for model training. However, in practice, obtaining a large number of annotations is prohibitively labor-intensive and even impossible. Co-training is a popular semi-supervised learning (SSL) paradigm, which trains multiple models based on a common training set while augmenting the limited amount of labeled data used for training each model via the pseudolabeled data generated from the prediction results of other models. Most of the existing co-training works do not control the quality of pseudolabeled data when using them. Therefore, the inaccurate pseudolabels generated by immature models in the early stage of the training process are likely to cause noticeable errors when they are used for augmenting the training data for other models. To address this issue, we propose a self-paced co-training for the GNN (SPC-GNN) framework for semi-supervised node classification. This framework trains multiple GNNs with the same or different structures on different representations of the same training data. Each GNN carries out SSL by using both the originally available labeled data and the augmented pseudolabeled data generated from other GNNs. To control the quality of pseudolabels, a self-paced label augmentation strategy is designed to make the pseudolabels generated at a higher confidence level to be utilized earlier during training such that the negative impact of inaccurate pseudolabels on training data augmentation, and accordingly, the subsequent training process can be mitigated. Finally, each of the trained GNN is evaluated on a validation set, and the best-performing one is chosen as the output. To improve the training effectiveness of the framework, we devise a pretraining followed by a two-step optimization scheme to train GNNs. Experimental results on the node classification task demonstrate that the proposed framework achieves significant improvement over the state-of-the-art SSL methods.

Utility of the Comprehensive Trail Making Test in the Assessment of Mild Cognitive Impairment in Older Patients.

The purpose of this study is to determine the usefulness of the CTMT (Comprehensive Trail Making Test) in diagnosing mild cognitive impairment in older patients. The test is used to assess executive functions, of which impairment is already observed in the early stages of the neurodegenerative process. The study includes 98 patients of a geriatric ward assigned to 2 groups of 49 patients each: patients diagnosed with a mild cognitive impairment and patients without a cognitive impairment, constituting the control group (group K). A set of screening tests was used in the initial study: the MMSE (Mini-Mental State Examination), MoCA (Montreal Cognitive Assessment), and CDT (Clock Drawing Test), GDS (Geriatric Depression Scale). The second study included the performance of the CTMT; the performance indicator was the time of performance. Statistically significant differences are obtained between patients with mild cognitive impairments and those in cognitive normality in the performance of the CTMT test (p < 0.01). Patients with MCIs took longer to complete all trails of the test. To identify cognitive impairment, cutoff points were proposed for the CTMT total score and the other test trails. The CTMT overall score and CTMT 5 scored the highest AUCs (CTMT overall score = 0.77, CTMT Trail 5 = 0.80). The Comprehensive Trail Making Test may be useful in diagnosing mild cognitive impairment as a complementary screening tool.

Impaired neural response to reward feedback in children with high schizotypal traits: Evidences from an ERP study

Reward processing deficit is a core feature of schizophrenia, however, it remains unclear whether reward processing is impaired in individuals with high schizotypy. In this study, 27 high schizotypal trait and 25 control group children were screened by the Chinese version of the Schizotypal Personality Questionnaire for Children (SPQC).We recorded their brain activity (event-related potentials, ERPs) while they completed a simple gambling task. In the early semi-automatic processing stage, small losses s evoked a more negative feedback-related negativity (FRN) in the high schizotypy group than that in control group, and the large wins evoked a less positive reward positivity (RewP) in the high schizotypy group than that in the control group. In the later cognitive appraisal stage, the Feedback-P3 (Fb-P3) amplitude was smaller in the schizotypy group than in control group. These results provided evidence that the abnormalities of outcome evaluation exist in the schizotypy children. Pending replications and longitudinal studies, the FRN, RewP and the P3 might represent a psychophysiological marker of risk for schizophrenia.

Effect of Neuromuscular Fatigue on the Countermovement Jump Characteristics: Basketball-Related High-Intensity Exercises.

Yoshida, N, Hornsby, WG, Sole, CJ, Sato, K, and Stone, MH. Effect of neuromuscular fatigue on the countermovement jump characteristics: basketball related high-intensity exercises. J Strength Cond Res XX(X): 000-000, 2023-The purpose of this study was to investigate basketball specific neuromuscular (NM) fatigue effect on countermovement jump (CMJ) force-time (F-T) curve characteristics. Eleven male college-level basketball athletes performed 6 CMJ trials at 3 baseline (pre) and 6 postexercise time points. The fatiguing protocol consisted of high-intensity basketball related exercises commensurate with basketball game or practice. Typical CMJ (CMJ-TYP) and phase-specific CMJ variables were derived from the F-T curve. Meaningful differences in CMJ performance were examined using effect size (ES) compared with baseline and previous postexercise time point. Baseline with 3 separated measurements demonstrated suitable CMJ variables reproducibility (CV, coefficient of variation). Most CMJ-TYP output and performance variables displayed substantial alterations immediately postexercise (0 hour) and returned to baseline at 24 hours postexercise, whereas the time and rate-related CMJ-TYP and CMJ-phase variables tended to display delayed decline peaked at 2 hours and delayed recovery to baseline at 48 hours postexercise. In conjunction with the return of the time and rate-related variables, CMJ performance displayed supercompensation at 72 hours postexercise. The results indicate altered NM functions with desired CMJ performance, such as jump height, which imply an altered movement strategy at early stage of recovery process. Full recovery may take 48-72 hours. Practitioners are, therefore, advised to monitor variables reflecting NM functions for precise manipulation of the intensity and volume of exercise to avoid prolonging the recovery from NM fatigue.