bluuebunny/crossref_metadata_2025 huggingface dataset:
Intimate relationships and hypnosis: insecure adult attachment affects emotions and absorption during hypnosis
Authors: Di Filippo Gloria , Perri Rinaldo Livio
Published: February 2024

Introduction

Hypnosis research indicates that subjects are not equally hypnotizable. Most studies on hypnotizability focused on the relationships with personality or cognitive variables. At the same time, only a few proposed the contribution of the attachment style, defined as the result of the childhood relationship with the caregivers and influencing the adult relations.

Methods

In the present investigation, two studies were carried out to test the possible association between adult attachment and hypnotic responsivity. The adult attachment was assessed using the Experiences in Close Relationships-Revised (ECR-R) questionnaire, while hypnosis was assessed through the Harvard Group Scale of Hypnotic Susceptibility (HGSHS:A; Study 1) and the Phenomenology of Consciousness Inventory: Hypnotic Assessment Procedure (PCI-HAP; Study 2) in order to adopt a behavioral and a phenomenological approach, respectively.

Results

Analyses showed that attachment factors (anxiety and avoidance) were not associated with the level of hypnotizability, whereas it was associated with variations of consciousness during hypnosis, mainly internal dialogue, absorption and negative emotions. Overall, the insecure attachment styles yielded increased mind wandering and restlessness during hypnosis when compared to the secure style. The reason probably lies in the feeling of anxiety or danger of insecurely attached individuals when involved in intimate or confidential relationships.

Conclusion

These findings clarify a still poorly investigated aspect concerning the influence of attachment style on hypnotic experience and further highlight the need to consider inter-individual differences and the phenomenological perspective when assessing hypnosis and hypnotizability.
No evidence for relationship between paternal post-partum depressive symptoms and testosterone or cortisol in first-time fathers
Authors: Kotov Daria A. , Corpuz Randy
Published: February 2024

Male life history strategies are regulated by the neuroendocrine system. Testosterone (T) and cortisol regulate male behaviors including parenting and facilitate managing tradeoffs at key transitions in development such as first-time fatherhood. Both hormones demonstrate marked fluctuations in the postnatal period, and this presents an opportunity to investigate the role of T and cortisol in postpartum depressive symptoms—comparably less studied in fathers than in mothers in the evolutionary literature. Prior work on depressive symptoms has yet to integrate insights from the “dual hormone hypothesis (DHH)” which has focused on how T and cortisol interact to jointly regulate traits associated with dominance and status-seeking (i.e., mating effort) but has yet to be included in models of parenting effort. In this research, we use secondary data to investigate the relationship between DHH and traits ostensibly opposed to status seeking (i.e., depressive symptoms). First-time fathers (n = 193) provided morning saliva samples 10 months following parturition and reported on the presence of depressive symptoms (BDI-II). Responses were decomposed into three factors: cognitive, affective, and somatic. Using hybrid latent variable structural equation modeling, we did not find evidence that T predicted variability in cognitive, affective, or somatic depressive symptom factors. We found a null effect for cortisol as well. Finally, we could not find evidence that the DHH variable (T × cortisol interaction) predicted any variability in cognitive, affective, or somatic depressive symptoms. While we did not find evidence to support our hypotheses using a secondary data set, this study contributes to research on the neuroendocrinology of depression in fathers. Discussion focuses on the limitations of sample demographics, timing of saliva and self-report collection, and the lack of extant theory specific to paternal postpartum depression.
Efficacy and safety of non-invasive brain stimulation in combination with antidepressants in adolescents with depression: a systematic review and meta-analysis
Authors: Li Yaoyao , Liu Xiaoyan
Published: February 2024

Objective

Non-invasive brain stimulation (NIBS) is beneficial to adult patients with depression, but its safety and efficacy in combination with antidepressants in children and adolescents with depression are not clear. We conducted a preliminary meta-analysis to objectively evaluate its clinical effect and provide information for future research and clinical practice.

Methods

PubMed, Cochrane Library, Embase, and Web of Science were searched systematically to find clinical trials published in English before April 11, 2023. Stata software was used for meta-analysis, and random or fixed effect models were used to combine effect sizes.

Results

Nine studies were eligible and included (n = 393). No articles about children were included in the analysis. The results showed that the remission rate was 40% (95% confidence interval [CI]: 13% to 71%). The scores of Children’s Depression Rating Scale (CRDS) and Hamilton’s depression scale (HAMD) significantly decreased compared to baseline value (MD = -27.04, 95% CI: -30.95, -23.12 and MD = -12.78, 95% CI: -19.55 to -6.01). In addition, the incidence of all adverse events was 13% (95% CI: 5%, 23%), and all were minor pain-related events.

Conclusion

The combination of NIBS and antidepressants has been shown to notably alleviate depressive symptoms in adolescents, offering a considerable level of safety. This therapeutic synergy is particularly effective in patients with major depressive disorder, where repetitive transcranial magnetic stimulation augmented with antidepressants can enhance the amelioration of depressive symptoms.

Systematic review registration

https://www.crd.york.ac.uk/prospero/display_record.php?ID=CRD42023442215, PROSPERO CRD42023442215.
Investigating amplitude of low-frequency fluctuation and possible links with cognitive impairment in childhood and adolescence onset schizophrenia: a correlation study
Authors: Liang Yinghui , Shao Rongrong , Xia Yanhong , Li Yadi , Guo Suqin
Published: February 2024

Background

Cognitive impairment (CI) is a distinctive characteristic of schizophrenia, with evidence suggesting that childhood and adolescence onset schizophrenia (CAOS), representing severe but rare forms of schizophrenia, share continuity with adult-onset conditions. While relationships between altered brain function and CI have been identified in adults with schizophrenia, the extent of brain function abnormalities in CAOS remains largely unknown. In this study, we employed resting-state functional magnetic resonance imaging (rs-fMRI) to investigate functional alterations in brain areas among patients with CAOS. To assess CI across multiple cognitive domains, we utilized the Stroop Color and Word Tests (SCWT) and MATRICS Consensus Cognitive Battery (MCCB) tests. Our objective was to explore the associations between functional CI and the amplitude of low-frequency fluctuation (ALFF) levels in these patients.

Methods

We enrolled 50 patients diagnosed with CAOS and 33 healthy controls (HCs) matched for sex and age. Cognitive functions were assessed using the MCCB and SCWT methods. Rs-fMRI data were acquired using gradient-echo echo-planar imaging sequences. Voxel-based ALFF group maps were compared through two-sample t-tests in SPM8. Subsequently, correlation analyses were conducted to identify associations between ALFF levels and cognitive scores.

Results

In comparison to HCs, patients exhibited significantly increased ALFF levels in the right fusiform gyrus, frontal lobe, and caudate, as well as the left frontal lobe and caudate. Conversely, reduced ALFF levels were observed in the temporal and left medial frontal lobes. Significant differences were identified between HCs and patients in terms of total cognitive scores, ALFF levels, and domain scores. All test scores were decreased, except for TMA. Correlation analyses between ALFF levels and cognitive functions in patients with CAOS differed from those in HCs. Pearson correlation analyses revealed positive associations between Brief Visuospatial Memory Test - Revised (BVMT-R) scores and ALFF levels in the left medial frontal gyrus. Digital Span Test (DST) scores were negatively correlated with ALFF levels in the right caudate, and Maze Test values were negatively correlated with levels in the left caudate. However, Pearson correlation analyses in HCs indicated that color and Hopkins Verbal Learning Test (HVLT-R) scores positively correlated with ALFF levels in the left frontal lobe, while color-word and symbol coding scores negatively correlated with levels in the right caudate.

Conclusions

Altered ALFF levels in the brain may be linked to cognitive impairment (CI) in patients with CAOS. We highlighted the pathophysiology of schizophrenia and provide imaging evidence that could potentially aid in the diagnosis of CAOS.
Long-term impact of resilience and extraversion on psychological distress during the COVID-19 pandemic: a longitudinal investigation among individuals with and without mental health disorders
Authors: Schmit Anna , Schurr Timo , Frajo-Apor Beatrice , Pardeller Silvia , Plattner Barbara , Tutzer Franziska , Conca Andreas , Fronthaler Martin , Haring Christian , Holzner Bernhard , Huber Markus , Marksteiner Josef , Miller Carl , Perwanger Verena , Pycha Roger , Schmidt Martin , Sperner-Unterweger Barbara , Hofer Alex
Published: February 2024

Background

Over the past years, the COVID-19 pandemic has caused significant disruptions in daily routines. Although the pandemic has affected almost everyone, it has been particularly challenging for people with pre-existing mental health conditions. Therefore, this study investigated the long-term impact of resilience and extraversion on psychological distress in individuals diagnosed with mental health disorders (MHD) compared to the general population. In addition, possible gender-specific differences were investigated.

Methods

123 patients with pre-existing MHD and 343 control subjects from Austria and Italy participated in three online surveys that had been conducted after the initial wave of the COVID-19 pandemic (t0), during the second lockdown in both countries (t1), and one year thereafter (t2). Participants completed standardized questionnaires on psychological distress (Brief-Symptom-Checklist), resilience (Resilience Scale), and extraversion (Big Five Inventory). A mediation model was employed to test the primary hypothesis. Possible gender-specific differences were analyzed using a moderated mediation model.

Results

The prevalence of psychological distress was consistently higher in patients compared to controls (t0: 37.3% vs. 13.2%, t1: 38.2% vs 11.7%, t2: 37.4% vs. 13.1%). This between-group difference in psychological distress at the first follow-up was fully mediated by baseline resilience scores (65.4% of the total effect). During the second-follow up, extraversion accounted for 18% of the total effect, whereas resilience slightly decreased to 56% of the total effect. Gender was not a significant moderator in the model.

Conclusion

Next to showing that people with MHD were particularly affected by the pandemic, these findings indicate that higher degrees of resilience and extraversion are related to less long-term psychological distress. Our findings stress the relevance of strengthening resilience and extraversion and to provide mental health support in times of crises, both to patients with MHD and the general population.
Risk assessment of psychiatric complications in infectious diseases: CALCulation of prognostic indices on example of COVID-19
Authors: Sorokin Mikhail , Markin Kirill , Trufanov Artem , Bocharova Mariia , Tarumov Dmitriy , Krasichkov Alexander , Shichkina Yulia , Medvedev Dmitriy , Zubova Elena
Published: February 2024

Introduction

Factors such as coronavirus neurotropism, which is associated with a massive increase in pro-inflammatory molecules and neuroglial reactivity, along with experiences of intensive therapy wards, fears of pandemic, and social restrictions, are pointed out to contribute to the occurrence of neuropsychiatric conditions.

Aim

The aim of this study is to evaluate the role of COVID-19 inflammation-related indices as potential markers predicting psychiatric complications in COVID-19.

Methods

A total of 177 individuals were examined, with 117 patients from a temporary infectious disease ward hospitalized due to COVID-19 forming the experimental group and 60 patients from the outpatient department showing signs of acute respiratory viral infection comprising the validation group. The PLR index (platelet-to-lymphocyte ratio) and the CALC index (comorbidity + age + lymphocyte + C-reactive protein) were calculated. Present State Examination 10, Hospital Anxiety and Depression Scale, and Montreal Cognitive Assessment were used to assess psychopathology in the sample. Regression and Receiver operating characteristic (ROC) analysis, establishment of cutoff values for the COVID-19 prognosis indices, contingency tables, and comparison of means were used.

Results

The presence of multiple concurrent groups of psychopathological symptoms in the experimental group was associated (R² = 0.28, F = 5.63, p < 0.001) with a decrease in the PLR index and a simultaneous increase in CALC. The Area Under Curve (AUC) for the cutoff value of PLR was 0.384 (unsatisfactory). For CALC, the cutoff value associated with an increased risk of more psychopathological domains was seven points (sensitivity = 79.0%, specificity = 69.4%, AUC = 0.719). Those with CALC > 7 were more likely to have disturbances in orientation (χ² = 13.6; p < 0.001), thinking (χ² = 7.07; p = 0.008), planning ability (χ² = 3.91; p = 0.048). In the validation group, an association (R²McF = 0.0775; p = 0.041) between CALC values exceeding seven points and the concurrent presence of pronounced anxiety, depression, and cognitive impairments was demonstrated (OR = 1.52; p = 0.038; AUC = 0.66).

Discussion

In patients with COVID-19, the CALC index may be used for the risk assessment of primary developed mental disturbances in the context of the underlying disease with a diagnostic threshold of seven points.
Young adults’ views on the mechanisms underpinning the impact of pets on symptoms of anxiety and depression
Authors: Hawkins Roxanne D. , Kuo Chih-Hsin , Robinson Charlotte
Published: February 2024

Introduction

Emerging adulthood is considered a peak age for the onset of mental health difficulties with approximately 75% of mental health disorders being diagnosed during this developmental period. Companion animals confer both risk and benefits to mental health yet the potential underpinning mechanisms which explain such impacts are not fully understood. This study aimed to gather an in-depth understanding of young adults’ lived experience of how their companion dogs and cats may impact their mental health symptoms and the perceived mechanisms which explain their effects.

Methods

Semi-structured interviews were carried out with 16 young adults aged 18-26 years, from the United Kingdom, who either had a companion dog, cat, or both. All participants had difficulties with anxiety and or depression, and 12 had received a formal diagnosis of an affective disorder.

Results

Five overarching themes and one subtheme were identified through reflexive thematic analysis using an inductive approach: Theme 1: Pet impact on generalized anxiety and panic, Subtheme 1A: Pet impact on social anxiety and loneliness; Theme 2: Pet impact on low mood, depression, and stress; Theme 3: Pet impact on severe mental health and suicide prevention; Theme 4: Staying well; Theme 5: Positive outlook and successful futures. Several perceived mechanisms underpinning the impacts of pets for mental health were also identified.

Discussion

These findings have relevance for the development and evaluation of mental health interventions and treatment protocols aimed at young adults with mental health difficulties, where companion animals may prove to be effective for symptom management and improvements in positive wellbeing.
Efficacy and acceptability of psilocybin for primary or secondary depression: A systematic review and meta-analysis of randomized controlled trials
Authors: Fang Shuping , Yang Xin , Zhang Wei
Published: February 2024

Introduction

Psilocybin is a classic psychedelics, which has been shown to have antidepressant effects by many studies in recent years. In this study, we aim to evaluate the efficacy, acceptability and tolerability of psilocybin in the treatment of primary (major depressive disorder) or secondary (experiencing distress related to life-threatening diagnoses and terminal illness) depression.

Methods

We searched PubMed, EMBASE, Web of Science, Cochrane Library and ClinicalTrials.gov for clinical trials of psilocybin for depression (updated to 4 October, 2023). Effect size Hedges’ g was used as an indicator of efficacy, and other outcomes included response rate, drop-out rate, and adverse events.

Results

A total of 10 studies were finally included in systematic review. 8 studies were included in the meta-analysis, involving a total of 524 adult patients, and produced a large effect size in favor of psilocybin (Hedge’s g =-0.89, 95% CI -1.25~-0.53, I² = 70.19%, P<0.01). The therapeutic effects of psilocybin increase with increasing doses. Adverse events caused by psilocybin are generally transient and reversible, but serious adverse events also may occur.

Discussion

Our study shows that psilocybin has both short-term and long-term antidepressant effects and holds promise as a potential complementary or alternative therapy for depression, probably. Further research may reveal more about its therapeutic potential.
Management and outcome of adult generalized tetanus in a Chinese tertiary hospital
Authors: An Yuling , Guo Yi , Li Lijuan , Li Ziyu , Fan Mingming , Peng You , Yi Xiaomeng , Lv Haijin
Published: February 2024

Background

Tetanus is a rare surgical infectious disease with a high reported relevant mortality. It still remains a serious problem in public health, particularly in low-income and middle-income countries. The purpose of this study was to investigate the management and prognosis of adult generalized tetanus in our hospital.

Methods

A total of 20 adult generalized tetanus patients were recruited in this retrospective observational study. Patients were retrieved from the hospital data base via discharge diagnosis. Patients were divided into two groups (Severe or Non-severe tetanus group) based on the severity of tetanus by using the Ablett classification. The differences between the two groups were compared.

Results

The study included 11 males (55%) and 9 females (45%). All tetanus patients recovered. The median age was 53.5 years [IQR: 19–78]. There were 1 mild (Grade 1) case (5%),5 moderate (Grade 2) cases (25%), 2 severe (Grade 3) cases (10%), and 12 very severe (Grade 4) cases (60%). Nineteen patients (95%) did not have tetanus immunization before. The majority of patients were farmers (60%), and came from rural areas (60%). Thirteen (65%) patients had a history of puncture injury. The rate of wound debridement after admission was 60% overall. Thirteen (65%) patients required mechanical ventilation for a median of 21 [IQR:12–41] days. Autonomic instability occurred in 13 (65%) patients. Pulmonary infections occurred in 12 (60%) patients. Median duration of hospital stay was 29.5 [IQR:12–68] days. More patients in the Severe group needed ICU admission, wound debridement, mechanical ventilation and heavy sedation combined with muscle relaxants (p < 0.05). The hospital stay was significantly longer in patients in the Severe group (p < 0.05).

Conclusion

After effective treatment, all adult patients with generalized tetanus in this study were cured and discharged. Severe tetanus requires early ICU treatment, wound debridement and effective treatment of autonomic instability.
Navigating a climate of administrative burden: the perspectives of young adult undocumented immigrants in applying for COVID-19 disaster relief assistance for immigrants in California
Authors: Ling Irving C. , Choi Hye Young , Sudhinaraset May
Published: February 2024

Undocumented immigrants experienced high levels of economic insecurity during the COVID-19 pandemic while being excluded from government-based relief and unemployment benefits. In April 2020, California became the first state to offer financial aid to undocumented immigrants through the innovative Disaster Relief Assistance for Immigrants (DRAI) program in collaboration with several community-based organizations (CBOs). However, the process of applying for aid was marked by many implementation challenges, such as intake and language access; however, little data exists on the direct experiences of the undocumented community. This qualitative study examines the experiences of undocumented Asian and Latinx young adults living in California in applying for DRAI through framework of administrative burden. Themes distilled from participant experiences highlight how administrative burden via learning, psychological, and compliance costs shape the ways in which undocumented immigrants navigate policies and programs, such as DRAI. These experiences highlight the need for policymakers to address structural and programmatic administrative burdens in policy development; failure to do so result in detrimental impacts that outweigh financial benefits or cause communities to forgo needed resources.
Implementation of an in-field IoT system for precision irrigation management
Authors: Dong Younsuk , Werling Benjamin , Cao Zhichao , Li Gen
Published: February 2024

Due to the impact of climate change on agriculture and the emergence of water security issues, proper irrigation management has become increasingly important to overcome the challenges. The Internet of Things (IoT) technology is being utilized in agriculture for collecting field information and sharing it through websites in real time. This study discusses the efforts taken to develop an IoT-based sensor station, a user-friendly website, and a smartphone app for irrigation management. In addition, the demonstration of the IoT-based sensor station and its effectiveness are discussed. Before deploying the sensor station, soil moisture sensor calibration was conducted using a laboratory experiment. Overall, the calibrated soil moisture sensors met the statistical criteria for both sand [root mean squared error (RMSE) = 0.01 cm3/cm3, index of agreement (IA) = 0.97, and mean bias error (MBE) = 0.01] and loamy sand (RMSE = 0.023 cm3/cm3, IA = 0.98, and MBE = −0.02). This article focuses on case studies from corn, blueberry, and tomato fields in Michigan, USA. In the corn and blueberry fields, the evaluation of irrigation practices of farmer's using an IoT-based sensor technology was considered. In the tomato field, a demonstration of automation irrigation was conducted. Overirrigation was observed using the IoT-based sensor station in some fields that have sandy soil and use a drip irrigation system. In the blueberry demonstration field, the total yield per plant (p = 0.025) and 50-berry weights (p = 0.013) were found to be higher with the recommended irrigation management than the farmer's existing field. In the tomato demonstration field, there were no statistical differences in the number of marketable tomatoes (p = 0.382) and their weights (p = 0.756) between the farmer's existing method and the recommended irrigation strategy. However, 30% less water was applied to the recommended irrigation strategy plot. Thus, the result showed that the IoT-based sensor irrigation strategy can save up to 30% on irrigation while maintaining the same yields and quality of the product.
Prevalence and Factors Associated With Frailty Among Older Adults Living With HIV Compared to Their Uninfected Peers From the Kenyan Coast
Authors: Mwangala Patrick N. , Nasambu Carophine , Wagner Ryan G. , Newton Charles R. , Abubakar Amina
Published: February 2024

Objectives: a) To document the prevalence and correlates of frailty among older adults living with HIV (OALWH) and their uninfected peers, and b) Investigate HIV status as an independent predictor of frailty.

Methods: This cross-sectional study was conducted between 2020 and 2021 at the Kenyan coast among 440 older adults aged ≥50 years (257 OALWH). Frailty was assessed using the Reported Edmonton Frail Scale. Logistic regression was used to examine the correlates of frailty.

Results: The prevalence of frailty was significantly higher among OALWH (24%) than their uninfected peers (13%). HIV seropositivity was not independently associated with frailty. Sleeping difficulties, ageism, higher waist/hip ratio, visiting traditional healers, HIV treatment change/interruption, prolonged illness following HIV diagnosis, and self-reported diabetes were significantly associated with higher odds of frailty. Residing in larger households, having higher income, having friends, being male and light physical activities were significantly associated with reduced odds of frailty.

Conclusion: The prevalence of frailty is elevated among OALWH; however, factors other than HIV are predominant, particularly psychosocial factors. Multicomponent interventions are needed to prevent/delay and manage frailty in this setting.
Stacked Multiscale Densely Connected Temporal Convolutional Attention Network for Multi-Objective Speech Enhancement in an Airborne Environment
Authors: Huang Ping , Wu Yafeng
Published: February 2024

Airborne speech enhancement is always a major challenge for the security of airborne systems. Recently, multi-objective learning technology has become one of the mainstream methods of monaural speech enhancement. In this paper, we propose a novel multi-objective method for airborne speech enhancement, called the stacked multiscale densely connected temporal convolutional attention network (SMDTANet). More specifically, the core of SMDTANet includes three parts, namely a stacked multiscale feature extractor, a triple-attention-based temporal convolutional neural network (TA-TCNN), and a densely connected prediction module. The stacked multiscale feature extractor is leveraged to capture comprehensive feature information from noisy log-power spectra (LPS) inputs. Then, the TA-TCNN adopts a combination of these multiscale features and noisy amplitude modulation spectrogram (AMS) features as inputs to improve its powerful temporal modeling capability. In TA-TCNN, we integrate the advantages of channel attention, spatial attention, and T-F attention to design a novel triple-attention module, which can guide the network to suppress irrelevant information and emphasize informative features of different views. The densely connected prediction module is used to reliably control the flow of the information to provide an accurate estimation of clean LPS and the ideal ratio mask (IRM). Moreover, a new joint-weighted (JW) loss function is constructed to further improve the performance without adding to the model complexity. Extensive experiments on real-world airborne conditions show that our SMDTANet can obtain an on-par or better performance compared to other reference methods in terms of all the objective metrics of speech quality and intelligibility.
An Energy Efficiency Optimization Method for Electric Propulsion Units during Electric Seaplanes’ Take-Off Phase
Authors: Wang Shuli , Li Ziang , Zhang Qingxin
Published: February 2024

The electric seaplane, designed for take-off and landing directly on water, incorporates additional structures such as floats to meet operational requirements. Consequently, during the take-off taxiing phase, it encounters significantly higher aerodynamic and hydrodynamic resistance than other aircraft. This increases energy demand for the electric seaplane during the take-off phase. A mathematical model for energy consumption during this stage was developed by analyzing resistance, using the propeller pitch angle as an optimization variable. This study proposes a coupled energy efficiency optimization method for the take-off phase of an electric seaplane’s electric propulsion unit (EPU). The method aims to determine an optimal propeller pitch angle configuration aligned with the seaplane’s design criteria. This ensures that the propeller output thrust meets minimal requirements during take-off while enhancing energy efficiency. Experimental validation with the two-seater electric seaplane prototype RX1E-S has demonstrated that selecting the optimal propeller pitch angle can effectively reduce energy consumption by approximately 10.4%, thereby significantly enhancing flight efficiency.
Phytoplasma-Induced Leaf Reddening as a Monitoring Symptom of Apple Proliferation Disease with Regard to the Development of Remote Sensing Strategies
Authors: Jarausch Wolfgang , Runne Miriam , Schwind Nora , Jarausch Barbara , Knauer Uwe
Published: February 2024

Apple proliferation (AP) is an economically important disease in many apple-growing regions caused by ‘Candidatus Phytoplasma mali’ which is spread by migrating psyllid vectors on a regional scale. As infected trees in orchards are the only inoculum source, the early eradication of those trees is one of the most efficient strategies to prevent further spread of AP. Remote sensing is a promising rapid and cost-effective tool to identify infected trees on a regional scale. AP-induced premature leaf reddening was evaluated as a reliable symptom for remote sensing by monitoring more than 20,000 trees in 68 different orchards with 20 representative cultivars from 2019 to 2022 in a highly AP-affected region in Southwest Germany. Specific AP symptoms were almost 100% correlated with molecular detection of ‘Ca. P. mali’ and these specific symptoms were almost 100% correlated with leaf reddening. ‘Ca. P. mali’ was detected in 71–97% of trees which showed partial or entire reddening without any other AP symptom. Experimental and field data showed that reddening was induced by cold night and warm day temperatures (about 5 °C vs. 20 °C) in September. Quantification of the phytoplasma by real-time PCR showed no correlation with the intensity of reddening in the leaf. PCR-RFLP subtyping revealed no influence of different ‘Ca. P. mali’ strains on the symptom expression. In conclusion, leaf reddening in late September/early October was a reliable symptom useful for remote sensing of AP.
Retroviral Insertion Polymorphism (RIP) of Porcine Endogenous Retroviruses (PERVs) in Pig Genomes
Authors: Du Zhanyu , Chen Cai , Zheng Yao , Wang Xiaoyan , Song Chengyi
Published: February 2024

Endogenous retroviruses (ERVs) are one of the superfamilies of long terminal repeat retrotransposons (LTRs) in mice and humans. Approximately 8% of the pig genome is composed of sequences derived from LTRs. While the majority of ERVs in pigs have decayed, a small number of full-length copies can still mobilize within the genome. This study investigated the unexplored retroviral insertion polymorphisms (RIPs) generated by the mobilization of full-length ERVs (Fl-ERVs), and evaluated their impact on phenotypic variation to gain insights into the biological role of Fl-ERVs in pigs. Overall, 39 RIPs (insertions or deletions relative to the pig reference genome) generated by Fl-ERVs were predicted by comparative genomic analysis, and 18 of them were confirmed by PCR detection. Four RIP sites (D5, D14, D15, and D18) were further evaluated by population analysis, and all of them displayed polymorphisms in multiple breeds. The RIP site of ERV-D14, which is a Fl-ERV inserted in the STAB2-like gene, was further confirmed by sequencing. Population analysis of the polymorphic site of ERV-D14 reveals that it presents moderate polymorphism information in the Large White pig breed, and the association analysis reveals that the RIP of ERV-D14 is associated with age variations at 30 kg body weight (p < 0.05) and 100 kg body weight (p < 0.01) in the population of Large White pigs (N = 480). Furthermore, the ERV-D14 RIP is associated with changes in the expression of the target gene STAB2-like in the liver, backfat, and leaf fat in Sushan pigs. These data suggest that some Fl-ERVs are still mobilizing in the pig’s genome, and contribute to genomic and phenotypic variations.
THz Data Analysis and Self-Organizing Map (SOM) for the Quality Assessment of Hazelnuts
Authors: Greco Manuel , Giarnetti Sabino , Giovenale Emilio , Taschin Andrea , Leccese Fabio , Doria Andrea , Senni Luca
Published: February 2024

In recent years, the use of techniques based on electromagnetic radiation as an investigative tool in the agri-food industry has grown considerably, and between them, the application of imaging and THz spectroscopy has gained significance in the field of food quality control. This study presents the development of an experimental setup operating in transmission mode within the frequency range of 18 to 40 GHz, which was specifically designed for assessing various quality parameters of hazelnuts. The THz measurements were conducted to distinguish between healthy and rotten hazelnut samples. Two different data analysis techniques were employed and compared: a traditional approach based on data matrix manipulation and curve fitting for parameter extrapolation, and the utilization of a Self-Organizing Map (SOM), for which we use a neural network commonly known as the Kohonen neural network, which is recognized for its efficacy in analyzing THz measurement data. The classification of hazelnuts based on their quality was performed using these techniques. The results obtained from the comparative analysis of coding efforts, analysis times, and outcomes shed light on the potential applications of each method. The findings demonstrate that THz spectroscopy is an effective technique for quality assessment in hazelnuts, and this research serves to clarify the suitability of each analysis technique.
Impact of Incorporating Two Types of Dried Raspberry Pomace into Gluten-Free Bread on Its Nutritional and Antioxidant Characteristics
Authors: Pecyna Anna , Krzywicka Monika , Blicharz-Kania Agata , Buczaj Agnieszka , Kobus Zbigniew , Zdybel Beata , Domin Marek , Siłuch Dariusz
Published: February 2024

The purpose of this study was to determine the impact of the pomace drying methods (freeze-drying and convection-drying) and their percentage (0–10%) on selected physicochemical properties of gluten-free bread. The contents of nutrients (protein, fiber, fat, ash, and carbohydrates), bioactive compounds, antioxidant properties, acidity, baking efficiency, and moisture of the obtained products were determined. Fortifying the bread with raspberry pomace resulted in a change in fiber content from 18.13% d. b. (control sample) up to 19.97% d. b. (10% of freeze-dried pomace), and a change in the fat and ash content in the bread from 5.74% and 2.83% d. b. (control sample) to 7.18% and 3.12% d. b. (10% of freeze-dried pomace). The content of carbohydrates decreased after adding raspberry pomace to the bread, from 65.71% d. b. (control sample) to 63.68% d. b. (5% of freeze-dried pomace). The research carried out also showed that the introduction of 10% freeze-dried raspberry pomace increased the total polyphenol content by 81.75% and the antioxidant properties defined by the ABTS method by 159.54% and by the DPPH method by 96.43% compared to the control bread. The introduction of pomace resulted in a significant reduction in the total baking loss, from 15.1% to 10.62%, and an increase in the total titratable acidity of the crumb, from 2.13 mL NaOH/10 g d. b to 7.78 mL NaOH/10 g d. b. Principal component analysis highlighted a marked effect of the drying method and content of raspberry pomace on the quality values of gluten-free bread. This research demonstrated that raspberry pomace can be a valuable source of fiber and bioactive substances in gluten-free bread.
Machine Learning-Supported Designing of Human–Machine Interfaces
Authors: Bántay László , Abonyi János
Published: February 2024

The design and functionality of the human–machine interface (HMI) significantly affects operational efficiency and safety related to process control. Alarm management techniques consider the cognitive model of operators, but mainly only from a signal perception point of view. To develop a human-centric alarm management system, the construction of an easy-to-use and supportive HMI is essential. This work suggests a development method that uses machine learning (ML) tools. The key idea is that more supportive higher-level HMI displays can be developed by analysing operator-related events in the process log file. The obtained process model contains relevant data on the relationship of the process events, enabling a network-like visualisation. Attributes of the network allow us to solve the minimisation problem of the ideal workflow–display relation. The suggested approach allows a targeted process pattern exploration to design higher-level HMI displays with respect to content and hierarchy. The method was applied in a real-life hydrofluoric acid alkylation plant, where a proposal was made about the content of an overview display.
A Low-Cost and High-Efficiency Active Cell-Balancing Circuit for the Reuse of EV Batteries
Authors: Dinh Minh-Chau , Le Thi-Tinh , Park Minwon
Published: February 2024

In this paper, a high-efficiency and low-cost active cell-to-cell balancing circuit for the reuse of electric vehicle (EV) batteries is proposed. In the proposed method, a battery string is divided into two legs to transfer the charge from each cell in one leg to that in the other and a bidirectional CLLC resonant converter is used to transfer energy between the selected cells. Thanks to the proposed structure, the number of bidirectional switches and gate drivers can be reduced by half compared to the conventional direct cell-to-cell topologies, thereby achieving lower cost for the system. The CLLC converter is used to transfer the charge, and it is designed to work at resonant frequencies to achieve zero-voltage zero-current switching (ZVZCS) for all the switches and diodes. Consequently, the system’s efficiency can be enhanced, and hence, the fuel economy of the system can also be improved significantly. To verify the performance of the proposed active cell-balancing system, a prototype is implemented for balancing the three EV battery modules that contain twelve lithium-ion batteries from xEV. The maximum efficiency achieved for the charge transfer is 89.4%, and the balancing efficiency is 96.3%.
Leveraging Artificial Intelligence to Expedite Antibody Design and Enhance Antibody–Antigen Interactions
Authors: Kim Doo Nam , McNaughton Andrew D. , Kumar Neeraj
Published: February 2024

This perspective sheds light on the transformative impact of recent computational advancements in the field of protein therapeutics, with a particular focus on the design and development of antibodies. Cutting-edge computational methods have revolutionized our understanding of protein–protein interactions (PPIs), enhancing the efficacy of protein therapeutics in preclinical and clinical settings. Central to these advancements is the application of machine learning and deep learning, which offers unprecedented insights into the intricate mechanisms of PPIs and facilitates precise control over protein functions. Despite these advancements, the complex structural nuances of antibodies pose ongoing challenges in their design and optimization. Our review provides a comprehensive exploration of the latest deep learning approaches, including language models and diffusion techniques, and their role in surmounting these challenges. We also present a critical analysis of these methods, offering insights to drive further progress in this rapidly evolving field. The paper includes practical recommendations for the application of these computational techniques, supplemented with independent benchmark studies. These studies focus on key performance metrics such as accuracy and the ease of program execution, providing a valuable resource for researchers engaged in antibody design and development. Through this detailed perspective, we aim to contribute to the advancement of antibody design, equipping researchers with the tools and knowledge to navigate the complexities of this field.
A Multi-Objective Sine Cosine Algorithm Based on a Competitive Mechanism and Its Application in Engineering Design Problems
Authors: Liu Nengxian , Pan Jeng-Shyang , Liu Genggeng , Fu Mingjian , Kong Yanyan , Hu Pei
Published: February 2024

There are a lot of multi-objective optimization problems (MOPs) in the real world, and many multi-objective evolutionary algorithms (MOEAs) have been presented to solve MOPs. However, obtaining non-dominated solutions that trade off convergence and diversity remains a major challenge for a MOEA. To solve this problem, this paper designs an efficient multi-objective sine cosine algorithm based on a competitive mechanism (CMOSCA). In the CMOSCA, the ranking relies on non-dominated sorting, and the crowding distance rank is utilized to choose the outstanding agents, which are employed to guide the evolution of the SCA. Furthermore, a competitive mechanism stemming from the shift-based density estimation approach is adopted to devise a new position updating operator for creating offspring agents. In each competition, two agents are randomly selected from the outstanding agents, and the winner of the competition is integrated into the position update scheme of the SCA. The performance of our proposed CMOSCA was first verified on three benchmark suites (i.e., DTLZ, WFG, and ZDT) with diversity characteristics and compared with several MOEAs. The experimental results indicated that the CMOSCA can obtain a Pareto-optimal front with better convergence and diversity. Finally, the CMOSCA was applied to deal with several engineering design problems taken from the literature, and the statistical results demonstrated that the CMOSCA is an efficient and effective approach for engineering design problems.
Teleoperated Grasping Using Data Gloves Based on Fuzzy Logic Controller
Authors: Lu Chunxiao , Jin Lei , Liu Yufei , Wang Jianfeng , Li Weihua
Published: February 2024

Teleoperated robots have attracted significant interest in recent years, and data gloves are one of the commonly used devices for their operation. However, existing solutions still encounter two challenges: the ways in which data gloves capture human operational intentions and achieve accurate mapping. In order to address these challenges, we propose a novel teleoperation method using data gloves based on fuzzy logic controller. Firstly, the data are collected and normalized from the flex sensors on data gloves to identify human manipulation intentions. Then, a fuzzy logic controller is designed to convert finger flexion information into motion control commands for robot arms. Finally, experiments are conducted to demonstrate the effectiveness and precision of the proposed method.
An Overview of UBTF Neuroregression Syndrome
Authors: Braden Anneliesse A. , Xiao Jianfeng , Hori Roderick , Brown Chester , Khan Mohammad Moshahid
Published: February 2024

Recently, a recurrent de novo dominant mutation in UBTF (c.628G>A, p.Glu210Lys; UBTF E210K) was identified as the cause of a neurological disorder which has been named UBTF Neuroregression Syndrome (UNS), or Childhood-Onset Neurodegeneration with Brain Atrophy (CONDBA). To date, only 17 cases have been reported worldwide. The molecular etiology is a pathogenic variant, E210K, within the HMG-box 2 of Upstream Binding Transcription Factor (UBTF). UBTF, a nucleolar protein, plays an important role in ribosomal RNA (rRNA) synthesis, nucleolar integrity, and cell survival. This variant causes unstable preinitiation complexes to form, resulting in altered rDNA chromatin structures, rRNA dysregulation, DNA damage, and ultimately, neurodegeneration. Defining clinical characteristics of the disorder include but are not limited to developmental regression beginning at approximately three years of age, progressive motor dysfunction, declining cognition, ambulatory loss, and behavioral problems. Histological and neuroimaging abnormalities include cortical atrophy, white matter deficits, and enlarged ventricles. Herein, we present a detailed overview of all published cases as well as the functional roles of UBTF to better understand the pathophysiology. Bringing undiagnosed cases to the attention of clinicians and researchers by making them aware of the clinical features will improve research and support the development of therapeutic interventions.
Effects of Adjunct Questions on L2 Reading Comprehension with Texts of Different Types
Authors: Sun Yunmei , Zhou Wenhui , Tang Shifang
Published: February 2024

Answering text-related questions while reading is a questioning strategy which is called adjunct questions or embedded questions, the benefits of which have been established in first-language reading as to enhance comprehension. The present study aims to study the effects different adjunct questions exert on second-language (L2) readers’ comprehension of texts of various types. One hundred and forty-four intermediate-level Chinese EFL learners participated in this study and were divided randomly into six groups. Each group was given either a narrative or an expository text with ‘what or why’ questions or no questions. A brief topic familiarity questionnaire was attached to the end of each text paper. The results showed that inserted adjunct questions improved the readers’ reading comprehension both in expository and narrative texts, but only narrative texts inserted with why questions had significant effects on the L2 reading comprehension. The findings suggested that text types and question types modulate the effects of inserted adjunct questions on the English reading of intermediate learners. Pedagogical implications and suggestions for future studies are provided.
A Recipe for Successful Metastasis: Transition and Migratory Modes of Ovarian Cancer Cells
Authors: Śliwa Aleksandra , Szczerba Anna , Pięta Paweł Piotr , Białas Piotr , Lorek Jakub , Nowak-Markwitz Ewa , Jankowska Anna
Published: February 2024

One of the characteristic features of ovarian cancer is its early dissemination. Metastasis and the invasiveness of ovarian cancer are strongly dependent on the phenotypical and molecular determinants of cancer cells. Invasive cancer cells, circulating tumor cells, and cancer stem cells, which are responsible for the metastatic process, may all undergo different modes of transition, giving rise to mesenchymal, amoeboid, and redifferentiated epithelial cells. Such variability is the result of the changing needs of cancer cells, which strive to survive and colonize new organs. This would not be possible if not for the variety of migration modes adopted by the transformed cells. The most common type of metastasis in ovarian cancer is dissemination through the transcoelomic route, but transitions in ovarian cancer cells contribute greatly to hematogenous and lymphatic dissemination. This review aims to outline the transition modes of ovarian cancer cells and discuss the migratory capabilities of those cells in light of the known ovarian cancer metastasis routes.