Miracle-dz/UniFAR-FTUs huggingface dataset:
Perceiving rejection by others: Relationship between rejection sensitivity and the spontaneous neuronal activity of the brain

ABSTRACT Rejection sensitivity (RS) can be defined as the disposition of a person to anxiously expect, readily perceive, and intensely react to rejection. Individuals with high RS are likely to suffer from mental disorders. The association between individual differences in RS and spontaneous neuronal activity at resting state has not yet been investigated. In this study, resting state data were used to investigate the relationship between RS and spontaneous neuronal activity in a large sample of healthy men (137) and women (172). The participants completed the rejection sensitivity questionnaire and underwent resting-state magnetic resonance imaging scan. Multiple regression analysis was conducted to examine the correlation between the regional amplitude of low-frequency fluctuations (ALFF) and rejection sensitivity scores adjusted for age and sex. Results showed that the ALFF value in the subgenual anterior cingulate cortex (sgACC) was positively associated with RS. Furthermore, functional connectivity with the middle frontal gyrus was negatively correlated with RS when sgACC was used as the seed region. These findings suggest that the spontaneous neuronal activity of sgACC and its functional connectivity with the lateral prefrontal cortex which are involved in experiencing social exclusion and regulating negative emotions are associated with individual differences in RS.
Application of Convolutional Neural Network Framework on Generalized Spatial Modulation for Next Generation Wireless Networks

Application of Convolutional Neural Network Framework on Generalized Spatial Modulation for Next Generation Wireless Networks Akram Marseet Supervising Professor: Dr. Ferat Sahin A novel custom auto-encoder Complex Valued Convolutional Neural Network (AE-CVCNN) model is proposed and implemented using MATLAB for multiple-input-multiple output (MIMO) wireless networks. The proposed model is applied on two different generalized spatial modulation (GSM) schemes: the single symbol generalized spatial modulation SS − GSM and the multiple symbol generalized spatial modulation (MS-GSM). GSM schemes are used with Massive-MIMO to increase both the spectrum efficiency and the energy efficiency. On the other hand, GSM schemes are subjected to high computational complexity at the receiver to detect the transmitted information. High computational complexity slows down the throughput and increases the power consumption at the user terminals. Consequently, reducing both the total spectrum efficiency and energy efficiency. The proposed CNN framework achieves constant complexity reduction of 22.73% for SSGSM schemes compared to the complexity of its traditional maximum likelihood detector (ML). Also, it gives a complexity reduction of 14.7% for the MS-GSM schemes compared to the complexity of its detector. The performance penalty of the two schemes is at most 0.5 dB. Besides to the proposed custom AE CV-CNN model, a different ML detector′s formula for (SS −GSM) schemes is proposed that achieves the same performance as the traditional
SEED: A software tool and an active‐learning strategy for data structures courses

SEED is a software tool designed for Java consisting of a class library and a set of simulators to facilitate learning of the main data structures. The educational component is based on an active case‐solving methodology accompanied by a pedagogical strategy. This strategy allows for the development of a multilayer‐model‐programming work for the construction of basic and advanced applications in real domains and for integration of its use, development and operation assessment with data structures. The evaluation results of SEED as a pedagogical mediator in the issue of binary trees is presented. The evaluation indicates that students prefer to use SEED due to its simplicity and attractive GUIs which facilitate data structures learning.
A performance-complexity analysis of four suboptimal SDMA algorithms

Space division multiple access (SDMA) is a promising solution to improve the spectral efficiency of future mobile radio systems. However, finding the group of mobile stations (MSs) that maximizes the system capacity using SDMA is a complex combinatorial problem, which can only be assuredly solved through an exhaustive search (ES). Because an ES is usually too complex, several suboptimal SDMA algorithms have been proposed. SDMA algorithms mainly differ on the grouping metrics they employ to quantify the spatial compatibility among MSs and on the grouping algorithm used to build the SDMA groups while avoiding ESs. In this work, the performance-complexity trade-off of four SDMA algorithms is investigated in terms of the average system capacity they achieve and on the number of operations they require. Expressions for the computational complexity of the algorithms are presented and it is shown that the algorithms proposed by the authors by Maciel and Klein (2007) attain almost the same average system capacity with comparable or lower complexity than other algorithms considered for benchmarking.
Workload Alerts—Using Physiological Measures of Mental Workload to Provide Feedback During Tasks

Feedback is valuable for allowing us to improve on tasks. While retrospective feedback can help us improve for next time, feedback ‘in action’ can allow us to improve the outcome of on-going tasks. In this article, we use data from functional Near InfraRed Spectroscopy to provide participants with feedback about their mental workload levels during high-workload tasks. We evaluate the impact of this feedback on task performance and perceived task performance, in comparison to industry standard mid-task self-assessments, and explore participants’ perceptions of this feedback. In line with previous work, we confirm that deploying self-reporting methods affect both perceived and actual performance. Conversely, we conclude that our objective concurrent feedback correlated more closely with task demand, supported reflection in action, and did not negatively affect performance. Future work, however, should focus on the design of this feedback and the potential behaviour changes that will result.
The relationship between socioeconomic status and beverage consumption in children: The Cuenca Study.

INTRODUCTION beverage consumption constitutes a source of children's daily energy intake. Some authors have suggested that consumption of caloric beverages is higher in children with a low socioeconomic position because families limit their spending on healthy food in order to save money. OBJECTIVE the aim of this study was to explore the relationship between socioeconomic status and Spanish children's beverage consumption. METHODS a cross-sectional study was conducted in a sub-sample of 182 children (74 girls) aged 9-11 from the province of Cuenca (Spain). Beverage consumption was assessed using the YANA-C assessment tool, validated for HELENA study. Data for parental socioeconomic status were gathered by using self-reported occupation and education questions answered by parents and classified according to the scale proposed by the Spanish Society of Epidemiology. RESULTS beverage intake was higher in children belonging to a middle-status family than in those of upper socioeconomic status (p = 0.037). The energy from beverages was similar in most water intake categories, except for water from beverages (p = 0.046). Regarding other beverages categories, middle-status children had higher consumption levels. In contrast, lower status children drank more fruit juices and skimmed milk. All of these do not show statistically significant differences. CONCLUSIONS our study did not find significant associations between beverages consumption and socioeconomic status in children. In fact, intake for most beverage categories was higher in middle-status children than in both other socioeconomic groups. Future research is needed in order to identify this complex relation between socioeconomic inequality and beverage intake behavior.
Biocomposites from Polylactic Acid and Bacterial Cellulose Nanofibers Obtained by Mechanical Treatment

Bacterial cellulose nanofibers (BCNF), obtained by the mechanical disintegration of BC pellicles, were used without any surface treatment for the fabrication of poly(lactic acid) (PLA) nanocomposites by a melt compounding process. The addition of BCNF in different amounts improved both the Young’s modulus and tensile strength of PLA. A 22% increase in these properties was observed in the nanocomposite with 2 wt. % nanofibers, due to the BCNF network formed at this concentration and characterized by atomic force microscopy. BCNF addition also increased the crystallinity and thermal stability of PLA, which were evaluated by thermal analysis. Due to the high purity of BCNF and the environmental friendliness of melt processing, it was concluded that PLA/BCNF nanocomposites can be designed for biomedical field and food packaging.
Acute respiratory failure requiring mechanical ventilation in severe chronic obstructive pulmonary disease (COPD)

Abstract There are limited data on the epidemiology of acute respiratory failure necessitating mechanical ventilation in patients with severe chronic obstructive pulmonary disease (COPD). The prognosis of acute respiratory failure requiring invasive mechanical ventilation is believed to be grim in this population. The purpose of this study was to illustrate the epidemiologic characteristics and outcomes of patients with underlying severe COPD requiring mechanical ventilation. A retrospective study of patients admitted to a quaternary referral medical intensive care unit (ICU) between January 2008 and December 2012 with a diagnosis of severe COPD and requiring invasive mechanical ventilation for acute respiratory failure. We evaluated 670 patients with an established diagnosis of severe COPD requiring mechanical ventilation for acute respiratory failure of whom 47% were male with a mean age of 63.7 ± 12.4 years and Acute physiology and chronic health evaluation (APACHE) III score of 76.3 ± 27.2. Only seventy-nine (12%) were admitted with a COPD exacerbation, 27(4%) had acute respiratory distress syndrome (ARDS), 78 (12%) had pneumonia, 78 (12%) had sepsis, and 312 (47%) had other causes of respiratory failure, including pulmonary embolism, pneumothorax, etc. Eighteen percent of the patients received a trial of noninvasive positive pressure ventilation. The median duration of mechanical ventilation was 3 days (interquartile range IQR 2–7); the median duration for ICU length of stay (LOS) was 5 (IQR 2–9) days and the median duration of hospital LOS was 12 (IQR 7–22) days. The overall ICU mortality was 25%. Patients with COPD exacerbation had a shorter median duration of mechanical ventilation (2 vs 4 days; P = .04), ICU (3 vs 5 days; P = .01), and hospital stay (10 vs 13 days; P = .01). The ICU mortality (9% vs 27%; P < .001), and the hospital mortality (17% vs 32%; P = .004) for mechanically ventilated patients with an acute exacerbation of severe COPD were lower than those with other etiologies of acute respiratory failure. A 1-unit increase in the APACHE III score was associated with a 1% decrease and having an active cancer was associated with a 45% decrease in ICU survival (P < .001). A discharge home at the time of index admission was associated an increased overall survival compared with any other discharge location (P < .001). We report good early outcomes, but significant long-term morbidity in patients with severe COPD requiring invasive mechanical ventilation for acute respiratory failure. A higher APACHE score and presence of active malignancy are associated with a decrease in ICU survival, whereas a discharge home is associated with an increase in the overall survival.
Drag reduction by combination of flow control using inlet disturbance body and plasma actuator on cylinder model

Flow past a cylinder is one of the things that is very applicable in everyday life. But behind those facts, there is a problem in it namely the drag force which is adverse and needs to be reduced. This research was conducted to find solutions to reduce drag by using a mix of passive flow control of inlet disturbance body and active flow control from plasma actuators. This research uses a test model in the form of a cylinder of a diameter of 120 mm with Reynolds Number 15000, 41000, 62000 and was expected to reduce drag after a given combination of flow control. From the results shown, either inlet disturbance of body and plasma actuators as well as a combination of both the flow of control is capable of performing the reduction coefficient of drag up to 70,22% on a variation of the Reynolds Number 62000.
GANAX: A Unified MIMD-SIMD Acceleration for Generative Adversarial Networks

Generative Adversarial Networks (GANs) are one of the most recent deep learning models that generate synthetic data from limited genuine datasets. GANs are on the frontier as further extension of deep learning into many domains (e.g., medicine, robotics, content synthesis) requires massive sets of labeled data that is generally either unavailable or prohibitively costly to collect. Although GANs are gaining prominence in various fields, there are no accelerators for these new models. In fact, GANs leverage a new operator, called transposed convolution, that exposes unique challenges for hardware acceleration. This operator first inserts zeros within the multidimensional input, then convolves a kernel over this expanded array to add information to the embedded zeros. Even though there is a convolution stage in this operator, the inserted zeros lead to underutilization of the compute resources when a conventional convolution accelerator is employed. We propose the GANAX architecture to alleviate the sources of inefficiency associated with the acceleration of GANs using conventional convolution accelerators, making the first GAN accelerator design possible. We propose a reorganization of the output computations to allocate compute rows with similar patterns of zeros to adjacent processing engines, which also avoids inconsequential multiply-adds on the zeros. This compulsory adjacency reclaims data reuse across these neighboring processing engines, which had otherwise diminished due to the inserted zeros. The reordering breaks the full SIMD execution model, which is prominent in convolution accelerators. Therefore, we propose a unified MIMD-SIMD design for GANAX that leverages repeated patterns in the computation to create distinct microprograms that execute concurrently in SIMD mode. The interleaving of MIMD and SIMD modes is performed at the granularity of single microprogrammed operation. To amortize the cost of MIMD execution, we propose a decoupling of data access from data processing in GANAX. This decoupling leads to a new design that breaks each processing engine to an access micro-engine and an execute micro-engine. The proposed architecture extends the concept of access-execute architectures to the finest granularity of computation for each individual operand. Evaluations with six GAN models shows, on average, 3.6x speedup and 3.1x energy savings over Eyeriss without compromising the efficiency of conventional convolution accelerators. These benefits come with a mere ≈7.8% area increase. These results suggest that GANAX is an effective initial step that paves the way for accelerating the next generation of deep neural models.
Factor analysis of the DSM-III-R borderline personality disorder criteria in psychiatric inpatients.

OBJECTIVE The goal of this study was to examine the factor structure of the DSM-III-R criteria for borderline personality disorder in young adult psychiatric inpatients. METHOD The authors assessed 141 acutely ill inpatients with the Personality Disorder Examination, a semistructured diagnostic interview for DSM-III-R personality disorders. They used correlational analyses to examine the associations among the different criteria for borderline personality disorder and performed an exploratory factor analysis. RESULTS Cronbach's coefficient alpha for the borderline personality disorder criteria was 0.69. A principal components factor analysis with a varimax rotation accounted for 57.2% of the variance and revealed three homogeneous factors. These factors were disturbed relatedness (unstable relationships, identity disturbance, and chronic emptiness); behavioral dysregulation (impulsivity and suicidal/self-mutilative behavior); and affective dysregulation (affective instability, inappropriate anger, and efforts to avoid abandonment). CONCLUSIONS Exploratory factor analysis revealed three homogeneous components of borderline personality disorder that may represent personality, behavioral, and affective features central to the disorder. Recognition of these components may inform treatment plans.
Simulated Cholinergic Reinnervation of β (INS-1) Cells: Antidiabetic Utility of Heterotypic Pseudoislets Containing β Cell and Cholinergic Cell

Cholinergic neurons can functionally support pancreatic islets in controlling blood sugar levels. However, in islet transplantation, the level of cholinergic reinnervation is significantly lower compared to orthotopic pancreatic islets. This abnormal reinnervation affects the survival and function of islet grafts. In this study, the cholinergic reinnervation of beta cells was simulated by 2D and 3D coculture of INS-1 and NG108-15 cells. In 2D culture conditions, 20 mM glucose induced a 1.24-fold increase (p < 0.0001) in insulin secretion from the coculture group, while in the 3D culture condition, a 1.78-fold increase (p < 0.0001) in insulin secretion from heterotypic pseudoislet group was observed. Glucose-stimulated insulin secretion (GSIS) from 2D INS-1 cells showed minimal changes when compared to 3D structures. E-cadherin expressed in INS-1 and NG108-15 cells was the key adhesion molecule for the formation of heterotypic pseudoislets. NG108-15 cells hardly affected the proliferation of INS-1 cells in vitro. Heterotypic pseudoislet transplantation recipient mice reverted to normoglycemic levels faster and had a greater blood glucose clearance compared to INS-1 pseudoislet recipient mice. In conclusion, cholinergic cells can promote insulin-secreting cells to function better in vitro and in vivo and E-cadherin plays an important role in the formation of heterotypic pseudoislets.
Remote Ischemic Conditioning in Cerebral Diseases and Neurointerventional Procedures: Recent Research Progress

Cerebral ischemia and stroke are increasing in prevalence and are among the leading causes of morbidity and mortality in both developed and developing countries. Despite the progress in endovascular treatment, ischemia/reperfusion (IR) injury is an important contributor to post-surgical mortality and morbidity affecting a wide range of neurointerventional procedures. However, pharmacological recruitment of effective cerebral protective signaling has been largely disappointing to date. In remote ischemic conditioning (RIC), repetitive transient mechanical obstruction of vessels at a limb remote from the IR injury site protects vital organs from IR injury and confers infarction size reduction following prolonged arterial occlusion. Results of pharmacologic agents appear to be species specific, while RIC is based on the neuroprotective influences of phosphorylated protein kinase B, signaling proteins, nitric oxide, and transcriptional activators, the benefits of which have been confirmed in many species. Inducing RIC protection in patients undergoing cerebral vascular surgery or those who are at high risk of brain injury has been the subject of research and has been enacted in clinical settings. Its simplicity and non-invasive nature, as well as the flexibility of the timing of RIC stimulus, also makes it feasible to apply alongside neurointerventional procedures. Furthermore, despite nonuniform RIC protocols, emerging literature demonstrates improved clinical outcomes. The aims of this article are to summarize the potential mechanisms underlying different forms of conditioning, to explore the current translation of this paradigm from laboratory to neurovascular diseases, and to outline applications for patient care.
Concentrated photovoltaics, a case study

Concentrated Photovoltaics (CPV), once a niche technology, has now reached the maturity and reliability for large scale power generation. Especially in regions where temperatures are very high, the use of high efficiency triple junction solar cells with concentrating optics allows stable energy yield. Thus CPV can be seen as complementary and not in concurrence with silicon photovoltaics. The state of the art, the advantages and limitations of this technology will be shown. Among the main advantages of CPV is the possibility of a much higher energy supply, when compared to silicon photovoltaics, both comparing CPV and silicon with same area or the same installed power. The use of recycled and recyclable materials allows a more environmentally friendly production. The possibility to couple CPV with desalination facilities, energy storage will be analysed. As an example a case study of a CPV installation in Northern Italy is discussed. Here the use of mature technologies, derived from automotive and lighting sectors resulted in a simple and efficient module.
Supporting Decision-making Activities in Multi-Surface Learning Environments

Collaborative decision-making is one of the emphasized student skills required by educators from different domains including science, technology and society. Multi-surface environments (MSE) appear particularly well suited for such learning activities, with large shared surfaces dedicated to the overview of information and context awareness, while personal surfaces serve browsing and analytical purposes. In this study, we present the design of Pickit, a MSE tool supporting collaborative decision-making activities. We show how Pickit is used by four groups of high school students as part of a learning activity. We analyze students’ interactions with digital devices that are related to given phases of the decision making process. Our results show that MSE are particularly interesting for such learning activities as they enable to balance personal and group work. The introduction of personal devices (tablets) makes free riding more difficult, while enabling development of personal judgment. By using Pickit, students successfully made their decisions and meanwhile better knew about the decision-making process.
Regulatory signatures of liver regeneration distilled by integrative analysis of mRNA, histone methylation, and proteomics

The capacity of the liver to regenerate is likely to be encoded as a plasticity of molecular networks within the liver. By applying a combination of comprehensive analyses of the epigenome, transcriptome, and proteome, we herein depict the molecular landscape of liver regeneration. We demonstrated that histone H3 Lys-4 was trimethylated at the promoter regions of many loci, among which only a fraction, including cell-cycle-related genes, were transcriptionally up-regulated. A cistrome analysis guided by the histone methylation patterns and the transcriptome identified FOXM1 as the key transcription factor promoting liver regeneration, which was confirmed in vitro using a hepatocarcinoma cell line. The promoter regions of cell-cycle-related genes and Foxm1 acquired higher levels of trimethylated histone H3 Lys-4, suggesting that epigenetic regulations of these key regulatory genes define quiescence and regeneration of the liver cells. A quantitative proteome analysis of the regenerating liver revealed that conditional protein degradation also mediated regeneration-specific protein expression. These sets of informational resources should be useful for further investigations of liver regeneration.