bluuebunny/crossref_metadata_2025 huggingface dataset:
Longitudinal bidirectional associations between personality and becoming a leader
Authors: Asselmann Eva , Holst Elke , Specht Jule
Published: April 2022

Objective

Leaders differ in their personalities from non‐leaders. However, when do these differences emerge? Are leaders “born to be leaders” or does their personality change in preparation for a leadership role and due to increasing leadership experience?

Method

Using data from the German Socio‐Economic Panel Study, we examined personality differences between leaders (N = 2683 leaders, women: n = 967; 36.04%) and non‐leaders (N = 33,663) as well as personality changes before and after becoming a leader.

Results

Already in the years before starting a leadership position, leaders‐to‐be were more extraverted, open, emotionally stable, conscientious, and willing to take risks, felt to have greater control, and trusted others more than non‐leaders. Moreover, personality changed in emergent leaders: While approaching a leadership position, leaders‐to‐be (especially men) became gradually more extraverted, open, and willing to take risks and felt to have more control over their life. After becoming a leader, they became less extraverted, less willing to take risks, and less conscientious but gained self‐esteem.

Conclusions

Our findings suggest that people are not simply “born to be leaders” but that their personalities change considerably in preparation for a leadership role and due to leadership experience. Some changes are transient, but others last for a long time.
Personalized Neural Networks Underlie Individual Differences in Ethnic Identity Exploration and Resolution
Authors: Constante Kevin , Demidenko Michael I. , Huntley Edward D. , Rivas‐Drake Deborah , Keating Daniel P. , Beltz Adriene M.
Published: April 2022

This study examined how ethnic identity relates to large‐scale brain networks implicated in social interactions, social cognition, self‐definition, and cognitive control. Group Iterative Multiple Model Estimation (GIMME) was used to create sparse, person‐specific networks among the default mode and frontoparietal resting‐state networks in a diverse sample of 104 youths aged 17–21. Links between neural density (i.e., number of connections within and between these networks) and ethnic identity exploration and resolution were evaluated in the full sample. Ethnic identity resolution was positively related to frontoparietal network density, suggesting that having clarity about one’s ethnic group membership is associated with brain network organization reflecting cognitive control. These findings help fill a critical knowledge gap about the neural underpinnings of ethnic identity.
Virtual health care for children: Parental willingness to adopt virtual health‐care technologies
Authors: Lawrence Joanna , Measey Mary‐Anne , Hoq Monsurul , Hiscock Harriet , Rhodes Anthea
Published: April 2022

Aim

To understand parental awareness and appetite for virtual health modalities, including asynchronous communication and remote monitoring. To understand which socio‐demographic characteristics are associated with greater awareness and appetite for virtual health.

Methods

Nationally representative survey of Australian parents, recruited via an online panel in February 2021 as part of the Royal Children's Hospital National Child Health Poll. Participants were randomly selected from the consumer panel.

Results

1981 (59.4% response rate) parents completed the survey. 39.9% were aware of virtual health care, defined by digital technology and medical devices to support remote monitoring. Higher levels of awareness were associated with being male, having previous teleconsultation experience, higher education attainment and employment. Most parents reported an appetite for asynchronous communication using an app or website to either provide information prior to a consult (65.9%), provide a photo of a rash or similar (61.7%) or receive medical advice (58.1%). Appetite for wearable devices was similar at 59.9%.

Conclusions

Whilst awareness of virtual healthcare was low, appetite exists amongst Australian parents to use technology to support their child's health care. Health‐care models, which incorporate asynchronous communication or symptom monitoring through apps, are likely to be acceptable and offer an accessible and sustainable alternative to traditional face‐to‐face health care.
The multidimensionality of sleep in population‐based samples: a narrative review
Authors: van de Langenberg Sterre C. N. , Kocevska Desana , Luik Annemarie I.
Published: April 2022

The identification of optimal sleep duration recommendations for the general population has long been an important goal on the public health agenda, as both short and long sleep duration have been linked to unfavourable health outcomes. Yet, sleep is more than duration alone and can be described across multiple domains, such as timing, regularity, satisfaction, alertness, and efficiency. We reviewed observational population‐based studies that examined differences in age, sex, and origin across multiple dimensions of sleep. Reviewed literature suggests an increasing prevalence of insomnia symptoms, shorter and less deep sleep in old age. Overall, women report poorer sleep quality than men despite objective measures revealing shorter and more fragmented sleep in men. Minorities generally have poorer quantity and quality of sleep, but multi‐ethnic studies have reported mixed results regarding the subjective experience of sleep. In sum, effects of age, sex and origin differ across sleep dimensions, thereby suggesting that the multidimensionality of sleep and how these different aspects interact should be studied across individuals. Studies should include both self‐reported measures and objective assessments in diverse population‐based samples, as both aspects are important to understand sleep health in the general population. Data‐driven descriptions could provide researchers and clinicians with insights into how well individuals are sleeping and offer concrete targets for promotion of sleep health across the population.
Thromboelastography in obese horses with insulin dysregulation compared to healthy controls
Authors: Lovett Amy L. , Gilliam Lyndi L. , Sykes Benjamin W. , McFarlane Dianne
Published: April 2022

Background

Both obesity and metabolic syndrome are associated with hypercoagulability in people, increasing the risk of cardiovascular disease and thromboembolic events. Whether hypercoagulability exists in obese, insulin‐dysregulated horses is unknown.

Hypothesis/Objectives

To determine if coagulation profiles differ between healthy horses and those with obesity and insulin dysregulation.

Animals

Fifteen healthy horses (CON) and 15 obese, insulin‐dysregulated horses (OBID). Individuals were university or client owned.

Methods

Case‐control study. Obesity was defined as a body condition score (BCS) ≥7.5/9 (modified Henneke scale). Insulin dysregulation status was assessed by an oral sugar test (OST). Kaolin‐thromboelastography and traditional coagulation variables were compared between groups. The direction and strength of the association between coagulation variables and BCS and OST results were determined using Spearman's correlation.

Results

Thromboelastography variables MA (OBID: 69.5 ± 4.5 mm; CON: 64.8 ± 4.3 mm; P = .007) and G‐value (OBID: 11749 ± 2536 dyn/m2; CON: 9319 ± 1650 dyn/m2; P = .004) were higher in OBID compared to CON. Positive correlations between MA and BCS (R = 0.45, P = .01) and serum insulin (T0: R = 0.45, P = .01; T60: R = 0.39, P = .03), and G‐value and BCS (R = 0.46, P = .01), and serum insulin (T0: R = 0.48, P = .007; T60: R = 0.43, P = .02; T90: R = 0.38, P = .04) were present.

Conclusions and Clinical Importance

Obese, insulin‐dysregulated horses are hypercoagulable compared to healthy controls.
The impact of COVID‐19 on aquaculture in China and recommended strategies for mitigating the impact
Authors: Yuan Yuan , Miao Weimin , Yuan Xinhua , Dai Yunyun , Yuan Yongming , Gong Yunchong
Published: April 2022

We carried out a preliminary investigation to study the impact of COVID‐19 on aquaculture in China and identify the strategies and measures that have been taken by the Chinese Government. The investigation involved questionnaire surveys designed for all stakeholders along the industrial chain, including grow‐out farmers, seed producers, fish processors, fish traders, and feed companies engaged in the catfish sector in Hubei Province and the tilapia sector in Guangdong Province during the strict period of control and after these control measures were lifted. We also attempted to summarize the government interventions and measures taken by different stakeholders along the value chain to minimize the damage caused by COVID‐19 and support the recovery of different sectors in the aquaculture industry. We found that due to delayed harvesting, fish stocks were held‐up in ponds and normal farming was interrupted. Farmers and traders were more severely impacted by the pandemic than other sectors. Furthermore, a series of strategies and measures are recommended to cope with the pandemic and other similar risks in the future. We expect that this study will provide good evidence for international societies to support the aquaculture industry in minimizing the impact of the pandemic and the rapid recovery of the industry in the post‐pandemic period.
A fibre and phenolic-rich flour from Isabel grape by-products with stimulatory effects on distinct probiotics and beneficial impacts on human colonic microbiota in vitro
Authors: Silva F.A. , de Souza E.L. , Queiroga R.C.R.E. , Voss G.B. , Pintado M.M.E. , Vasconcelos M.A.S.
Published: April 2022

This study evaluated the effects of a fibre and phenolic-rich flour (IGF) prepared from Isabel grape by-products on the growth and metabolism of different probiotics and distinct bacterial populations part of the human intestinal microbiota during an in vitro colonic fermentation. IGF was submitted to simulated gastrointestinal digestion before use in the experiments. IGF favoured the growth of the probiotics Lactobacillus acidophilus La-05, L. casei L-26 and Bifidobacterium lactis Bb-12, with viable counts of >7 log CFU per ml, as well as caused decreases in pH values and increases in organic acid production in the growth medium during 48 h of cultivation. IGF increased the population of beneficial micro-organisms forming the human intestinal microbiota, particularly Lactobacillus spp., decreased the pH values, and increased the lactic acid and short-chain fatty acid (acetic, butyric and propionic acids) production during 24 h of in vitro colonic fermentation. These results indicate the potential prebiotic effects of IGF, which should represent a novel sustainable added-value ingredient with functional properties and gut-health benefits.
A case of chronic inflammatory demyelinating polyneuropathy following COVID‐19 vaccine
Authors: Katada Eiichi , Toyoda Takanari , Yamada Gohei , Morishima Akira , Matsukawa Noriyuki
Published: April 2022

We report a 44‐year‐old woman who presented with bilateral weakness of the hands and distal paresthesia of the arms on the next day of the second COVID‐19 vaccine, and gradually progressed ascending weakness of the arms and legs, and sensory ataxia beyond 2 months. She was diagnosed as a chronic inflammatory demyelinating polyneuropathy (CIDP) following COVID‐19 vaccine on the basis of clinical and electrophysiological findings. This is a first case diagnosed as a CIDP following COVID‐19 vaccine alone.
Guidewire‐assisted placement of water‐perfused esophageal high‐resolution manometry probe when gastric insertion fails: A single‐center experience
Authors: Delbaen Corinne , Gkolfakis Paraskevas , Devière Jacques , Blero Daniel , Louis Hubert
Published: April 2022

Background

Blind positioning of a high‐resolution manometry (HRM) probe across the esophagogastric junction (EGJ) is not always possible. We report our experience using guidewire‐assisted water‐perfused HRM probe insertion when the EGJ could not be traversed.

Methods

Retrospective study analyzing the failure rate of EGJ insertion during HRM, and reporting a series of guidewire‐assisted procedures.

Key Results

Among 2727 HRM procedures, the failure rate for traversing the EGJ was 2.7% (73 patients). The technique of guidewire‐assisted placement of the HRM probe was used in 25 patients; it was well‐tolerated and successful in all patients. No motility disorder was found in 6 patients. In four patients with previously diagnosed achalasia, achalasia subtype changed to type III in one patient. While a suspected motility disorder at barium esophagram and/or initial imperfect HRM tracing was confirmed in 10 patients, a new motility disorder was diagnosed in five patients using guidewire‐assisted placement of the HRM probe.

Conclusions and Inferences

In cases of inability to traverse the EGJ, insertion of a water‐perfused HRM probe using an endoscopically‐placed nasogastric guidewire allows successful EGJ and esophageal peristalsis assessment. Although motility disorders are often suspected using alternative diagnostic modalities, guidewire‐assisted placement of HRM may be helpful for revealing them in patients where alternative diagnostic modalities are either unavailable or inconclusive.
An integrated high‐resolution mapping shows congruent biodiversity patterns of Fagales and Pinales
Authors: Lyu Lisha , Leugger Flurin , Hagen Oskar , Fopp Fabian , Boschman Lydian M. , Strijk Joeri Sergej , Albouy Camille , Karger Dirk N. , Brun Philipp , Wang Zhiheng , Zimmermann Niklaus E. , Pellissier Loïc
Published: April 2022

The documentation of biodiversity distribution through species range identification is crucial for macroecology, biogeography, conservation, and restoration. However, for plants, species range maps remain scarce and often inaccurate.

We present a novel approach to map species ranges at a global scale, integrating polygon mapping and species distribution modelling (SDM). We develop a polygon mapping algorithm by considering distances and nestedness of occurrences. We further apply an SDM approach considering multiple modelling algorithms, complexity levels, and pseudo‐absence selections to map the species at a high spatial resolution and intersect it with the generated polygons.

We use this approach to construct range maps for all 1957 species of Fagales and Pinales with data compilated from multiple sources. We construct high‐resolution global species richness maps of these important plant clades, and document diversity hotspots for both clades in southern and south‐western China, Central America, and Borneo. We validate the approach with two representative genera, Quercus and Pinus, using previously published coarser range maps, and find good agreement.

By efficiently producing high‐resolution range maps, our mapping approach offers a new tool in the field of macroecology for studying global species distribution patterns and supporting ongoing conservation efforts.
Mathematics–gender stereotype endorsement influences mathematics anxiety, self‐concept, and performance differently in men and women
Authors: Rossi Serena , Xenidou‐Dervou Iro , Simsek Emine , Artemenko Christina , Daroczy Gabriella , Nuerk Hans‐Christoph , Cipora Krzysztof
Published: April 2022

Mathematics anxiety (MA) is negatively associated with mathematics performance. Although some aspects, such as mathematics self‐concept (M self‐concept), seem to modulate this association, the underlying mechanism is still unclear. In addition, the false gender stereotype that women are worse than men in mathematics can have a detrimental effect on women. The role that the endorsement of this stereotype (mathematics–gender stereotype (MGS) endorsement) can play may differ between men and women. In this study, we investigated how MA and mathematics self‐concept relate to arithmetic performance when considering one's MGS endorsement and gender in a large sample (n = 923) of university students. Using a structural equation modeling approach, we found that MA and mathematics self‐concept mediated the effect of MGS endorsement in both men and women. For women, MGS endorsement increased their MA level, while in men, it had the opposite effect (albeit weak). Specifically, in men, MGS endorsement influenced the level of the numerical components of MA, but, unlike women, it also positively influenced their mathematics self‐concept. Moreover, men and women perceived the questions included in the considered instruments differently, implying that the scores obtained in these questionnaires may not be directly comparable between genders, which has even broader theoretical and methodological implications for MA research.
In Defense of Constitutivism About Epistemic Normativity
Authors: Horst David
Published: April 2022

Epistemic constitutivism(EC ) holds that the nature of believing is such that it gives rise to a standard of correctness and that other epistemic normative notions (e.g., reasons for belief) can be explained in terms of this standard. If defensible, this view promises an attractive and unifying account of epistemic normativity. However,ECfaces a forceful objection: that constitutive standards of correctness are never enough for generating normative reasons. This paper aims to defendECin the face of this objection. I do so in two steps. First, I dispute a crucial assumption underlying the case againstEC: that constitutive standards of correctness in general are ‘reason‐giving’ only if and because there is also apriorreason to comply with them. Second, I outline a strategy of howECcan meet the challenge of explaining what's special about the activity of believing such that, unlike other standard‐governed activities, it is capable of generating normative reasons.
Evaluation of frailty, abuse and depression among community‐dwelling older adults in a nortwest city of Turkey
Authors: Akyol Guner Türkan
Published: April 2022

Background

This study aimed to evaluate the frailty, abuse, and depression experienced by community‐dwelling older adults and to raise awareness in society about the abuse of the elderly.

Methods

This cross‐sectional study was carried out in three family health centres in a city centre in the northwest of Turkey. The sample consisted of 429 older adults. Data were collected with Descriptive form, FRAIL Scale, Hwalek‐Sengstock Elder Abuse Screening Test, and the Geriatric Depression Scale Short Form. In data analysis, percentage, mean ± SD, t‐test, analysis of variance, Tukey test, Pearson correlation coefficient, and multiple regression analysis were used. The significance level in the tests was taken as P < 0.05.

Results

In this study, 28.68% of the elderly were in the fragile group, 22.84% experienced abuse and 24.0% were depressed. The elders who participated in the study were evaluated according to the scale scores used. It was determined that they were in the fragile group with a score of 2.21 + 1.47; they were exposed to low level of abuse with 1.58 + 1.17 points and they were depressed with 5.15 + 4.82 points. There was a high and positive significant correlation between the frailty and abuse experienced by the elderly (P < 0.001; r: 0.621), there was a middle and positive significant correlation between frailty and depression (P < 0.001; r: 0.492), and high and positive correlation were found between abuse and depression in the elderly (P < 0.001; r: 0.647).

Conclusions

This study shows that frailty, abuse, and depression are important problems in community‐dwelling older adults and there are significant relationships between them. In order to prevent the abuse that the elderly in the fragile group are exposed to, it is recommended that especially health workers should be trained on elder abuse in in‐service training programs.
Experiences of families of people living with frontotemporal dementia: a qualitative systematic review
Authors: Shiba Tamami , Yamakawa Miyae , Endo Yoshimi , Konno Rie , Tanimukai Satoshi
Published: April 2022

Frontotemporal dementia (FTD) is characterised by atrophy of the frontal and/or temporal lobes. People with FTD show language and emotional disturbances from onset, and communication problems usually affect people with FTD and their families even before diagnosis. These unique characteristics of FTD are not well understood and create substantial problems for people living with FTD and their families. This review explores the experiences of families of people living with FTD. Studies were selected and screened according to the Preferred Reporting Items for Systematic Reviews and Meta‐Analyses guidelines. We searched four bibliographic databases for articles up to February 2021 to identify qualitative data on the experiences of families. The Critical Appraisal Skills Programme checklist for qualitative studies was used to assess all included studies. Of 235 identified articles, we included six studies in the qualitative synthesis. Meta‐ethnography was conducted to interpret families' experiences of people living with FTD. The emergent concepts were synthesised into five themes: Something is wrong with my loved one; No one fully understands; Existential pain of caring for a loved one with FTD; Increased burden owing to specific FTD symptoms; and Forced to adapt to new and unique ways of living with a loved one with FTD. This review highlighted families' confusion and suffering (which began in the early stages of the disease, and sometimes before diagnosis) and the difficulty of communicating with people with FTD. These findings have implications for future practice, as they demonstrate the positive effect on family life of appropriate support that is provided early, rather than after the disease has progressed.
An online Trier social stress paradigm to evoke affective and cardiovascular responses
Authors: DuPont Caitlin M. , Pressman Sarah D. , Reed Rebecca G. , Manuck Stephen B. , Marsland Anna L. , Gianaros Peter J.
Published: April 2022

In response to the COVID‐19 pandemic, prior studies have modified the Trier Social Stress Test to be conducted remotely. The current study aimed to extend these studies to test whether a remote Trier Social Stress Test (rTSST) can elicit (a) affective, (b) blood pressure, and (c) heart rate responses relative to a control condition and whether these responses were reliable when assessed 1 week later. Participants (N = 99, 19.7 ± 3.5 years, 55% female) were randomized to a control or stress condition. Participants received blood pressure monitors in person. Controls completed easier versions of the tasks with a single, friendly researcher. Stress participants performed more difficult versions of the task in front of two judges who participants believed were rating their performance. Blood pressure and heart rate were measured every 2 min throughout, while affect was assessed at baseline, after the final task, and following recovery. The rTSST was feasible to administer with minimal technical issues reported. Participants reported lower positive affect and higher negative affect during the tasks in the stress condition relative to controls. Similarly, stress participants had higher cardiovascular responses during the tasks relative to controls, except that blood pressure was not elevated during mental arithmetic in stress participants relative to controls. Cardiovascular responses demonstrated good test–retest reliability when assessed 1 week later, especially when computed using area under the curve methods. Overall, a rTSST can be used to elicit affective and cardiovascular reactivity and provides an opportunity to increase the accessibility of research participation among diverse populations.
Shaky social insurance foundation: Income instability and pension participation in South Korea
Authors: Yen Wei‐Ting
Published: April 2022

Objective

Many welfare states in young democracies feature low effective social insurance coverage, especially in old‐age pension. What explains the ineffective coverage? This article shows individual income instability is a microlevel factor contributing to low effective coverage.

Method

The article used 15 waves of the Korean Labor Income Panel Study and constructed a fine‐grained individual‐level income instability measure, which was used to predict individual participation in state‐run public pension using (multinomial) logistic models with industry, occupation, and cohort fixed effects.

Result

The article shows that income instability is negatively associated with public pension participation, and the negative relationship becomes larger as income level increases. Moreover, income instability inhibits only participation in state‐led risk pooling, but not in private self‐insuring.

Conclusion

The article sheds light on disentangling an individual‐level factor buttressing young welfare states and bears implications for the future contour of welfare states in young democracies.
Trust in physicians and trust in government predict COVID‐19 vaccine uptake
Authors: Viskupič Filip , Wiltse David L. , Meyer Brittney A.
Published: April 2022

Objective

We consider how trust in government, trust in physicians, and interpersonal trust affect the likelihood of COVID‐19 vaccine uptake.

Methods

A survey of 3057 registered South Dakota voters was fielded in April 2021 that measured COVID‐19 vaccine uptake, three aspects of trust, and several other factors related to vaccine hesitancy. Logistic regression was utilized to analyze the responses.

Results

We found positive, statistically significant, and substantively impactful effects for trust in government and trust in physicians on the likelihood of COVID‐19 vaccine uptake, and null results for interpersonal trust.

Conclusions

Our findings provide a more nuanced understanding of the relationship between trust and COVID‐19 vaccine uptake, and suggest that public health official as well as physicians should strive to increase the public's trust in the medical community.
Jointly modeling bus and taxi ridership: A Bayesian multivariate spatial analysis accounting for cross‐ridership correlation
Authors: Luan Hui , Zhang Shanqi
Published: April 2022

Understanding the spatial patterns of transit ridership and their ascribable factors is critical for urban and transportation planning. Existing studies predominantly examine a single type of transit ridership but neglect important cross‐ridership correlation. This study aims to develop a Bayesian multivariate spatial modeling approach for jointly analyzing multiple ridership. In particular, cross‐ridership correlation is estimated using correlated spatially unstructured residuals, correlated spatial random effects, or the combination of both. The proposed approach is applied to a case study of Wuhu, China, where the correlation between bus and taxi ridership is accounted for in the modeling of transit ridership and their built environment determinants. Results show that accounting for cross‐ridership correlation significantly improves model‐fitting, but the fashion used to induce such a correlation matters. Furthermore, the role of built environment in determining transit ridership could be over‐estimated without considering cross‐ridership correlation. This study contributes to statistical modeling of transit ridership by applying a spatial multivariate approach, which can improve our understanding of the underlying processes of multiple ridership, their interactions, as well as their associations with physical environments.
Establishment of a new cell line of canine inflammatory mammary cancer: IMC‐118
Authors: Gao Hongbo , Zhou Han , Gao Yiming , He Lixin , Li Wenxuan , Xu Meixia , Feng Huili , Feng Xiujuan , Qiu Changwei
Published: April 2022

Canine inflammatory mammary cancer (IMC) has long been regarded as an attractive animal model for research into human inflammatory breast cancer (IBC), Although some canine mammary tumour cell lines corresponding to human mammary cancer cell lines have been established, there is still a need to supplement the canine mammary tumour cell bank. The goal of this study was to create a new type of IMC cell line. The primary tumour, IMC‐118, was identified as IMC by pathology examination. Immunohistochemistry analysis revealed negative immunoreactivity to oestrogen receptor (ER), but positive immunoreactivity to progesterone receptor (PR) and human epidermal growth factor receptor‐2 (HER‐2). Immunofluorescence (IF) analysis revealed that the IMC‐118 cell line from this primary tumour was negative for ER but positive for PR and HER‐2, and was also positive for epithelial and mesenchymal cell markers. This cell line was cultured stably for more than 50 passages and grew well after cryopreservation. In vivo, tumour masses and metastases in the lungs were discovered after inoculating the IMC‐118 cells into the nude mice model. As a result, a novel canine IMC cell line, IMC‐118, was effectively established, and could be employed as a promising model for immunotherapy and epithelial‐mesenchymal transition mechanism of IMC research in both dogs and humans.
Determination of Asymptotic Normalization Coefficients by Analytic Continuation of Differential Cross Sections
Authors: Blokhintsev L. D. , Savin D. A.
Published: April 2022

A method is discussed for determining the asymptotic normalization coefficients (ANC) using the analytic continuation of experimental differential cross sections for nuclear transfer reactions to the pole point of the reaction amplitude with respect to the variable $$\cos\theta$$, where $$\theta$$ is the scattering angle. Within the framework of this method, using experimental data on the differential cross section for the reaction $${}^{12}\textrm{C}(0^{+};0\textrm{ MeV})(d,p){}^{13}\textrm{C}(1/2^{+};3.09\textrm{ MeV})$$ the ANC for the channel $${}^{13}\textrm{C}(1/2^{+};3.09\textrm{ MeV})\to{}^{12}\textrm{C}(0^{+};0\textrm{ MeV})+n$$ was determined. When determining the ANC, the corrections caused by the Coulomb interaction in the initial, final and intermediate states of the reaction were taken into account. It is shown that these corrections significantly affect the extracted ANC value.
Fast Charged Particles in the Interaction of $${}^{{56}}$$Fe with Be, Ta, and U Nuclei at an Energy of 400 MeV
Authors: Penionzhkevich Yu. E. , Lukyanov S. M. , Maslov V. A. , Samarin V. V. , Aznabayev D. , Butusov I. V. , Issatayev T. , Mendibayev K. , Stukalov S. S. , Shakhov A. V.
Published: April 2022

The energy spectra of alpha particles emitted at an angle of 0$${}^{\circ}$$ in the interaction of 400-MeV $${}^{56}$$Fe ions with $${}^{238}$$U, $${}^{181}$$Ta, and $${}^{9}$$Be targets were measured by means of a high-resolution magnetic analyzer (MAVR, which is the acronym of the Russian name of this setup). The energy spectra of charged particles ranging from Li to Ne were also measured. The experimental data obtained in this way indicate that the emission of alpha particles is a dominant process in the above reactions. Particles of high energy, up to those in the vicinity of the so-called kinematical limit for two-body reactions, were observed with a rather high yield. The sensitivity of the experimental procedure that employed the aforementioned magnetic analyzer made it possible to observe events characterized by cross-section values smaller by six to eight orders of magnitude than that at the maximum of the spectrum. The cross section for the production of light particles is shown to be dependent on their binding energy in the target. The experimental data obtained in this study were analyzed with aid of the moving-source model.
Experimental constraints on the properties of $$P_c$$ states
Authors: Burns T. J. , Swanson E. S.
Published: April 2022

Using new experimental data on photoproduction and $$\Lambda _b^0$$

Λ
b
0

decays, we derive constraints on the properties of the LHCb $$P_c$$

P
c

states. We conclude that $$P_c(4312)$$

P
c

(
4312
)

, $$P_c(4380)$$

P
c

(
4380
)

and $$P_c(4440)$$

P
c

(
4440
)

can be described as $$\Sigma _c\bar{D}$$

Σ
c

D

¯

, $$\Sigma _c^*\bar{D}$$

Σ
c
∗

D

¯

and $$\Sigma _c\bar{D}^*$$

Σ
c

D

¯

∗

molecules, but that $$P_c(4457)$$

P
c

(
4457
)

does not fit into the same picture. Based on the apparent absence of additional partner states, and the striking disparity between $$\Lambda _c^+\bar{D}^0$$

Λ
c
+

D

¯

0

and $$\Lambda _c^+\bar{D}^{*0}$$

Λ
c
+

D

¯

∗
0

decays, we conclude that $$P_c(4440)$$

P
c

(
4440
)

has $$3/2^-$$

3
/

2
-

quantum numbers. Using heavy-quark symmetry we predict large experimental signals for $$P_c$$

P
c

states in $$\eta _c p K^-$$

η
c

p

K
-

, $$\Lambda _c^+\bar{D}^{*0}K^-$$

Λ
c
+

D

¯

∗
0

K
-

, and $$\Sigma _c^{(*)}\bar{D}K^-$$

Σ
c

(

∗
)

D

¯

K
-

. We also argue that current experimental data on photoproduction is almost at the level of sensitivity required to observe $$P_c$$

P
c

states.
Bayesian approach to inverse problems: an application to NNPDF closure testing
Authors: Del Debbio Luigi , Giani Tommaso , Wilson Michael
Published: April 2022

We discuss the Bayesian approach to the solution of inverse problems and apply the formalism to analyse the closure tests performed by the NNPDF collaboration. Starting from a comparison with the approach that is currently used for the determination of parton distributions (PDFs), we discuss some analytical results that can be obtained for linear problems and use these results as a guidance for more complicated non-linear problems. We show that, in the case of Gaussian distributions, the posterior probability density of the parametrized PDFs is fully determined by the results of the NNPDF fitting procedure. Building on the insight that we obtain from the analytical results, we introduce new estimators to assess the statistical faithfulness of the fit results in closure tests. These estimators are defined in data space, and can be studied analytically using the Bayesian formalism in a linear model in order to clarify their meaning. Finally we present results from a number of closure tests performed with current NNPDF methodologies. These further tests allow us to validate the NNPDF4.0 methodology and provide a quantitative comparison of the NNPDF4.0 and NNPDF3.1 methodologies. As PDFs determinations move into precision territory, the need for a careful validation of the methodology becomes increasingly important: the error bar has become the focal point of contemporary PDFs determinations. In this perspective, theoretical assumptions and other sources of error are best formulated and analysed in the Bayesian framework, which provides an ideal language to address the precision and the accuracy of current fits.
Circuit Manufacturing Defect Detection Using VGG16 Convolutional Neural Networks
Authors: Althubiti Sara A. , Alenezi Fayadh , Shitharth S. , K. Sangeetha , Reddy Chennareddy Vijay Simha
Published: April 2022

Manufacturing, one of the most valuable industries in the world, is boundlessly automatable yet still quite stuck in traditionally manual and slow processes. Industry 4.0 is racing to define a new era of digital manufacturing through Internet of Things- (IoT-) connected machines and factory systems, fully comprehensive data gathering, and seamless implementation of data-driven decision-making and action taking. Both academia and industry understand the tremendous value in modernizing manufacturing and are pioneering bleeding-edge strides every day to optimize one of the largest industries in the world. IoT production, functional testing, and fault detection equipment are already being used in today’s maturing smart factory paradigm to superintend intelligent manufacturing equipment and perform automated defect detection in order to enhance production quality and efficiency. This paper presents a powerful and precise computer vision model for automated classification of defect product from standard product. Human operators and inspectors without digital aid must spend inordinate amounts of time poring over visual data, especially in high volume production environments. Our model works quickly and accurately in sparing defective product from entering doomed operations that would otherwise incur waste in the form of wasted worker-hours, tardy disposition, and field failure. We use a convolutional neural network (CNN) with the Visual Geometry Group with 16 layers (VGG16) architecture and train it on the Printed Circuit Board (PCB) dataset with 3175 RBG images. The resultant trained model, assisted by finely tuned optimizers and learning rates, classifies defective product with 97.01% validating accuracy.
VNGuarder: An Internal Threat Detection Approach for Virtual Network in Cloud Computing Environment
Authors: Lin Li , Yang Huanzeng , Zhan Jing , Lv Xuhui
Published: April 2022

Edge-assisted Internet of things applications often need to use cloud virtual network services to transmit data. However, the internal threats such as illegal management and configuration to cloud platform intentionally or unintentionally will lead to virtual network security problems such as malicious changes of user network and hijacked data flow. It will eventually affect edge-assisted Internet of things applications. We propose a virtual network internal threat detection method called VNGuarder in a cloud computing environment, which can effectively monitor whether the virtual network configuration of legitimate users under the IaaS cloud platform has been maliciously changed or destroyed by insiders. First, based on the life cycle of cloud virtual network services, we summarized two types of internal attacks involving illegal use of virtualization management tools and illegal invocation of virtual network-related processes. Second, based on normal behavior of tenants, a hierarchical trusted call correlation scheme is proposed to provide a basis for discovering that insiders illegally call virtualized management tools and virtual network-related processes on the controller node of the cloud platform or the network node and compute node. Third, a trace-enable mechanism combining real-time monitoring and log analysis is introduced. By collecting and recording the complete call process of virtual network management and configuration in the cloud platform, and comparing it with the result of the hierarchical trusted call correlation, abnormal operations can be reported to the tenants in time. Comprehensive simulation experiments on the Openstack platform show that VNGuarder can effectively detect illegal management and configuration of virtual networks by insiders without significantly affecting the creation time of tenant networks and the utilization of CPU and memory.
Assessment of Occupational Burnout among Intensive Care Unit Staff in Jazan, Saudi Arabia, Using the Maslach Burnout Inventory
Authors: Shbeer Abdullah , Ageel Mohammed
Published: April 2022

Objective. ICU workers are among the healthcare staff exposed to high occupational burnout in their daily interactions with patients, especially during the COVID-19 pandemic. This study aimed to investigate the prevalence and risk factors of burnout among ICU staff in the Jazan region of Saudi Arabia. Methods. A cross-sectional study was conducted using the Maslach Burnout Inventory (MBI), which was distributed to ICU staff between August 1 and November 30, 2021. A total of 150 ICU workers were invited to participate in the study. Results. A total of 104 ICU staff responded to the survey (69% response rate), including 62 nurses, 30 physicians, and 12 respiratory therapists. Among the respondents, 63 (61%) were female and 41 (39%) were male. The mean scores for emotional exhaustion, depersonalization, and personal accomplishment were 22.44 ± 14.92, 9.18 ± 7.44, and 29.58 ± 12.53, respectively. The ICU staff at high risk of emotional exhaustion, depersonalization, and personal accomplishment were 36%, 28%, and 47%, respectively. The leading cause of burnout among ICU staff in the study was workload, and taking a vacation was the most cited coping mechanism for occupational burnout. Conclusion. ICU staff are at high risk of emotional exhaustion, depersonalization, and lack of personal accomplishment. Policymakers should implement regulations that ensure hospitals have adequate employees to reduce the workload that leads to occupational burnout.
Syntactic Knowledge Embedding Network for Aspect-Based Sentiment Classification
Authors: Wen Yan , Li Wenkai , Zeng Qingtian , Duan Hua , Zhang Feng , Kang Shitao
Published: April 2022

An aspect-based sentiment classification task is a fine-grained sentiment analysis task, which is aimed at identifying the sentiment polarity of a given aspect in subjective sentences. In recent years, some researchers have applied pretrained BERT models to this task. However, existing research only uses the BERT output layer and ignores the syntactic features in the middle layers, leading to deviations in the prediction results. In order to solve above problems, we propose a new model BERT-SFE. Firstly, we explicitly utilize the middle layers of BERT to capture the underlying syntactic features. Secondly, we construct a syntactic feature extraction unit based on Star-Transformer, which uses an auxiliary vector and the star network structure to capture both local and global syntactic information in a sentence. Finally, we merge the syntactic features with the semantic features from the BERT output layer in the feature fusion layer, obtaining a more accurate sentiment representation of the aspect. The experimental results on three public ABSA datasets show that using the syntactic feature extraction unit based on Star-Transformer to mine the syntactic knowledge in the middle layers of BERT can effectively improve the accuracy of sentiment classification. BERT-SFE achieves the best performance compared with existing models.
Application of Hidden Markov Model in Financial Time Series Data
Authors: Chang Qingqing , Hu Jincheng
Published: April 2022

Financial time series have typical characteristics such as outliers, trends, and mean reversion. The existence of outliers will affect the effectiveness of the unknown parameter estimation in the financial time series forecasting model, so that the forecasting error of the model will be larger. Quantitative forecasting methods are divided into causal forecasting method and time series forecasting method. The causal forecasting method uses the causal relationship between the predictor variable and other variables to predict, and the time series forecasting method infers the future value of the predictor variable based on the structure of the historical data of the predictor. Therefore, this paper proposes a hidden Markov model prediction method based on the observation vector sequence, which can simultaneously consider the influence of the variable sequence structure and related factors.
Effect of Deep Learning on College Students’ Career Planning
Authors: Gu Xianhui
Published: April 2022

It is difficult for college students to find jobs after graduation, which is the most important problem to be solved now. This paper chooses the statistical analysis method to analyze the career planning of college students under different circumstances. Four aspects are analyzed, which are decision-making action, current situation evaluation, career exploration, and self-understanding level. The main conclusions of this paper are as follows. In this study, the gender differences of college students have a certain impact on their career. Generally speaking, the career planning level of boys is higher than that of girls. The job-hunting needs of college graduates are students who enter social work. Family factors affect the level of college students’ career planning. It is found that students’ school experience is the most important factor affecting the level of career planning, and school experience is also reflected in whether students have class committee experience.
Bayesian Adaptive Lasso for the Partial Functional Linear Spatial Autoregressive Model
Authors: Xu Dengke , Tian Ruiqin , Lu Ying
Published: April 2022

This study introduces a partial functional linear spatial autoregressive model which can explore the relationship between a scalar spatially dependent response variable and predictive variables containing both multiple scalar covariates and a functional covariate. With approximating to the functional coefficient by Karhunen–Loève representation, we propose a Bayesian adaptive Lasso method to simultaneously estimate unknown parameters and select important covariates in the model, which can be performed by combining the Gibbs sampler and the Metropolis–Hastings algorithm. Some simulation studies are conducted and the results show that the proposed Bayesian method behaves well.
Foreign Muslim Workers’ Perspectives of the Basic Needs of Muslim-Friendly Tourist Services: An Empirical Analysis of a Non-Muslim Destination
Authors: Yen Huang-Ping , Chang Jing-Wen , Ho Kung-Cheng , Hung Hao-Kai
Published: April 2022

The rapid growth of Halal travel offers a tourism opportunity for countries, but non-Muslim countries often find it difficult to meet the multiple religious needs of Muslim tourists. This study verifies Muslim tourists’ requirements for basic hotel and food services and identifies the categories in which to place these attributes and which ones need resources to increase Muslim tourists’ satisfaction. Applying Taiwan as a non-Muslim destination, we surveyed 216 Indonesian Muslim foreign workers and used the recently developed Gradient Boosting Decision Trees, instead of a regression method, to overcome the nonlinear and multicollinearity issues of Penalty-Reward-Contrast Analysis. Impact-Range Performance Analysis and Asymmetric Impact-Performance Analysis were then applied to examine the basic attributes of Muslim foreign workers’ tourist experiences. We learned that using Gradient Boosting Decision Trees provided advantages over the regression method. Empirical results indicated that hotel-related factors are prioritized over food services when Muslim tourists visit a non-Muslim country. In addition, religious observances play an essential part in Muslim tourists’ hotel choices, and conveniently accessible Halal food is a desirable travel requisite for this group.
Probabilistic Evaluation of Hydraulic Fracture Performance Using Ensemble Machine Learning
Authors: Xu Xiaoping , Ma Xianlin , Zhan Jie
Published: April 2022

Evaluation of hydraulic fracture (HF) performances is critical to develop unconventional resources such as tight oil and gas. We present a probabilistic evaluation approach that integrates ensemble machine learning with Monte Carlo simulation. In the method, we employ the ensemble learning to develop a predictive model between well productivity and its influential factors including both geological properties and HF treatment parameters. Next, coupling the built prediction model with Monte Carlo simulation, an empirical cumulative probability distribution of the well productivity is generated. The well HF performance is assessed by estimating its cumulative probability value. The proposed method is applied to evaluate the HF performances in a developed block of the eastern Sulige region. The study shows that 19% of the wells were fractured with good quality and 55% of the wells were fractured with average quality, while the rest were stimulated with poor quality. The evaluations provide a guideline for optimization of HF designs of wells that have not been hydraulically stimulated in the region.
Study of Subfascial Endoscopic Perforator Surgery Combined with Endovenous Laser Treatment in the Treatment of Great Saphenous Varicose Veins
Authors: Wang Li , Du Jianqing , Zhang Hong
Published: April 2022

Great saphenous varicose vein (GSVV) is a venous reflux disease of the lower extremity. In order to explore the clinical effect of subfascial endoscopic perforator surgery (SEPS) with endovenous laser treatment (EVLT) in the treatment of GSVV, 80 patients who underwent unilateral saphenous varicose surgery are analyzed. The operation results show that the patients who used SEPS + EVLT have less operation time and mean blood loss, shorter postoperative active time and hospitalization stay, better curative effect, and higher notch aesthetics

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. SEPS combined with EVLT has a remarkable curative effect in the treatment of saphenous varicose veins of lower extremity, which can significantly shorten the hospitalization time of patients and improve the coagulation index and stress index.