Miracle-dz/UniFAR-FTUs huggingface dataset:
Opportunities for breaking an energy generation limit of photovoltaic using multijunction and super-multijunction cells

This paper discusses the potential of the power conversion efficiency of solar cells from various materials considering external radiative efficiency, open-circuit voltage loss. The possibility of the power conversion efficiency is summarized in the 1st chapter. The examined cells are Silicon, III-V, CIS, CdTe, Organic, Dye-sensitized and Perovskite. The 2nd and successive chapters discuss the potential of the multijunction cells. The power conversion efficiency can be raised by using multi-junction structure. However, fluctuation of the atmospheric parameters substantially impacts the energy yield. The calculation considering the variation of atmospheric parameters showed a dramatic decline of the annual energy yield from the cells with more than five junctions. Super-multijunction solar cells were proposed, and optimization work was done. The top and the bottom junctions have lower bandgap for buffering to the mismatching and collecting a full range of the sunlight by robust energy conversion, and the annual energy substantially increases even by five or six junctions.
Effect of soaking and microwave pretreatments on nutritional profile and cooking quality of different lentil cultivars.

The present study was planned to apply various cooking pretreatments for improvement in nutritional profile and cooking quality of some Pakistani lentil cultivars. For this purpose, four lentil cultivars were analyzed for physicochemical properties. All lentil varieties were subjected to soaking (1.5, 3.0 and 4.5 h) and microwave roasting (10, 20 and 30 sec) before cooking to find out impact on cooking time, anti-nutritional factors (tannins, phytic acid and trypsin inhibitor), in-vitro protein digestibility and the level of different minerals in control and treated samples. Mean square of each parameter revealed significant difference among different lentil varieties and the treatments applied. Overall there was 54.16, 48.47, 51.93 and 99.82% reduction were noted for cooking time, tannins, phytic acid and trypsin inhibitors of lentils subjected to soaking followed by cooking, respectively along with 72.01% improvement in in-vitro protein digestibility. Whereas comparatively less reduction in tannins, phytic acid and trypsin inhibitors were recorded for microwave roasted lentils as 30.67, 45.39 and 97.82%, respectively. Microwave treatments imparted less influence on in-vitro protein digestibility and cooking time in relation to soaking. Mineral losses were observed in all treated samples. However, maximum losses were observed for Zn (43.98%) and minimum for Cu (7.75%). Conclusively, soaking before cooking was found better than microwave roasting.
DeFine: deep convolutional neural networks accurately quantify intensities of transcription factor-DNA binding and facilitate evaluation of functional non-coding variants

Abstract The complex system of gene expression is regulated by the cell type-specific binding of transcription factors (TFs) to regulatory elements. Identifying variants that disrupt TF binding and lead to human diseases remains a great challenge. To address this, we implement sequence-based deep learning models that accurately predict the TF binding intensities to given DNA sequences. In addition to accurately classifying TF-DNA binding or unbinding, our models are capable of accurately predicting real-valued TF binding intensities by leveraging large-scale TF ChIP-seq data. The changes in the TF binding intensities between the altered sequence and the reference sequence reflect the degree of functional impact for the variant. This enables us to develop the tool DeFine (Deep learning based Functional impact of non-coding variants evaluator, http://define.cbi.pku.edu.cn) with improved performance for assessing the functional impact of non-coding variants including SNPs and indels. DeFine accurately identifies the causal functional non-coding variants from disease-associated variants in GWAS. DeFine is an effective and easy-to-use tool that facilities systematic prioritization of functional non-coding variants.
A longitudinal analysis of the attention networks in 6- to 11-year-old children

ABSTRACT Attention is critical for everyday functioning. Posner and Petersen’s model of attention describes three neural networks involved in attention control—the alerting network for arousal, the orienting network for selecting sensory input and reorienting attention, and the executive network for the regulatory control of attention. No longitudinal research has examined relative change in these networks in children. A modified version of the attention network task (ANT) was used to examine changes in the three attention networks, three times over 12 months, in 114 6-, 8- and 10-year-olds. Findings showed that the alerting network continued to develop over this period, the orienting network had stabilized by 6 years, and the conflict network had largely stabilized by 7 years. The reorienting of attention was also assessed using invalid cues, which showed a similar developmental trajectory to the orienting attention network and had stabilized by 6 years. The results confirm that age 6 to 7 years is a critical period in the development of attention, in particular executive attention. The largest improvement over the evaluation period was between 6 and 7 years; however, subtle changes were found in attention beyond 8 years of age.
A Psychometric Investigation of the Painful and Provocative Events Scale: Moving Forward

Acquired capability for suicide is posited to develop through repeated exposure to physically painful and psychologically provocative events; however, there is limited research evaluating the assessment of painful and provocative events. The current study examined the factor structure, validity, and reliability of the Painful and Provocative Events Scale (PPES). Categorical exploratory and confirmatory factor analyses were conducted in a sample of undergraduate students (N = 732). A 15-item PPES with a 3-factor solution best fits the data; however, both the subscales derived from factor analyses yielded inconsistent validity and reliability. Despite addressing limitations of previous psychometric investigations of the PPES, the inconsistent findings of the current study suggest the theoretical reconceptualization of painful and provocative events and the subsequent development of a valid and reliable assessment of painful and provocative events is needed to take the place of current versions of the PPES.
Knowledge and attitudes of dentists toward shortened dental arch therapy in Saudi Arabia.

OBJECTIVE The aim of this study was to assess and compare the knowledge and attitudes of dentists toward shortened dental arch (SDA) therapy in Saudi Arabia. MATERIALS AND METHODS In this cross-sectional study, self-designed-structured questionnaires were distributed among specialists (SP), residents (RES), and general dental practitioners (GDP) in Saudi Arabia. The questionnaire enquired about dentists' opinion regarding function, esthetic, and comfort in patients with SDA. It also enquired about the risks associated with SDA treatment (tooth wear, temporomandibular dysfunction (TMD), and tooth migration). Participants also graded SDA decision-making factors for their significance. Frequency distribution and Chi-square test were performed to compare the responses. RESULTS A total of 300 questionnaires were completed. 53.9% of SP applied SDA therapy in <10% of patients. However, 54.8% of RES and 46.6% of GDP never used SDA therapy. SDA was considered by dentists to provide a satisfactory or acceptable function (76.4%), esthetics (76.1%), and comfort (76.8%). There was a significant difference in opinions of SP, GDP, and RES, in relation to the effect of SDA on esthetics (P = 0.039), tooth-wear (P < 0.001), TMD (P < 0.001), and tooth migration (P = 0.002). CONCLUSION The knowledge of SP and GDP with regards to SDA therapy was broadly in line with current standards. Less than 10% of patients had objections towards SDA therapy. SDA therapy was clinically applied in fewer than 10% of cases.
Senescent cells and osteoarthritis: a painful connection

Senescent cells (SnCs) are associated with age-related pathologies. Osteoarthritis is a chronic disease characterized by pain, loss of cartilage, and joint inflammation, and its incidence increases with age. For years, the presence of SnCs in cartilage isolated from patients undergoing total knee artificial implants has been noted, but these cells’ relevance to disease was unclear. In this Review, we summarize current knowledge of SnCs in the multiple tissues that constitute the articular joint. New evidence for the causative role of SnCs in the development of posttraumatic and age-related arthritis is reviewed along with the therapeutic benefit of SnC clearance. As part of their senescence-associated secretory phenotype, SnCs secrete cytokines that impact the immune system and its response to joint tissue trauma. We present concepts of the immune response to tissue trauma as well as the interactions with SnCs and the local tissue environment. Finally, we discuss therapeutic implications of targeting SnCs in treating osteoarthritis.
ABC Transporters and Their Role in the Neoadjuvant Treatment of Esophageal Cancer

The prognosis of esophageal cancer (EC) is poor, despite considerable effort of both experimental scientists and clinicians. The tri-modality treatment consisting of neoadjuvant chemoradiation followed by surgery has remained the gold standard over decades, unfortunately, without significant progress in recent years. Suitable prognostic factors indicating which patients will benefit from this tri-modality treatment are missing. Some patients rapidly progress on the neoadjuvant chemoradiotherapy, which is thus useless and sometimes even harmful. At the same time, other patients achieve complete remission on neoadjuvant chemoradiotherapy and subsequent surgery may increase their risk of morbidity and mortality. The prognosis of patients ranges from excellent to extremely poor. Considering these differences, the role of drug metabolizing enzymes and transporters, among other factors, in the EC response to chemotherapy may be more important compared, for example, with pancreatic cancer where all patients progress on chemotherapy regardless of the treatment or disease stage. This review surveys published literature describing the potential role of ATP-binding cassette transporters, the genetic polymorphisms, epigenetic regulations, and phenotypic changes in the prognosis and therapy of EC. The review provides knowledge base for further research of potential predictive biomarkers that will allow the stratification of patients into defined groups for optimal therapeutic outcome.
MR imaging of the knee: findings in asymptomatic collegiate basketball players.

OBJECTIVE The purpose of our study was to evaluate the knees of asymptomatic high-level collegiate basketball players before the beginning of the basketball season to gain an understanding of nonclinical findings in this patient population. SUBJECTS AND METHODS Bilateral knee MR imaging examinations of 17 varsity basketball players (12 men and five women) were performed before basketball season began. All of the subjects were imaged on a 1.5-T magnet. The MR imaging studies were reviewed by two musculoskeletal radiologists. Structures analyzed were the menisci, ligaments, cartilage, plicae, and bone marrow. The presence of a joint effusion was also noted. RESULTS Fourteen (41%) of the 34 knees had bone marrow edema, eight (24%) showed signal in the patellar tendon, and 14 (41%) had abnormal cartilage signal or a focal abnormality. Twelve (35%) of the 34 knees showed a joint effusion. Two knees (6%) showed abnormal signal along the infrapatellar plica. Four knees (12%) were noted to have a discoid meniscus. CONCLUSION An MR examination of the knees of high-level collegiate basketball players may show changes unique to this population. The changes seen on MR imaging in these athletes may be asymptomatic abnormalities. For instance, changes suggestive of patellar tendinopathy were identified in these asymptomatic subjects.
Individuality-preserving Silhouette Extraction for Gait Recognition

Most gait recognition approaches rely on silhouette-based representations due to high recognition accu- racy and computational efficiency, and a key problem for those approaches is how to accurately extract individuality- preserved silhouettes from real scenes, where foreground colors may be similar to background colors and the back- groundis cluttered. We thereforeproposea method of individuality-preservingsilhouetteextractionfor gait recognition using standard gait models (SGMs) composed of clean silhouette sequences of a variety of training subjects as a shape prior. We firstly match the multiple SGMs to a background subtraction sequence of a test subject by dynamic pro- gramming and select the training subject whose SGM fit the test sequence the best. We then formulate our silhouette extraction problem in a well-established graph-cut segmentation framework while considering a balance between the observed test sequence and the matched SGM. More specifically, we define an energy function to be minimized by the following three terms: (1) a data term derived from the observed test sequence, (2) a smoothness term derived from spatio-temporally adjacent edges, and (3) a shape-prior term derived from the matched SGM. We demonstrate that the proposed method successfully extracts individuality-preserved silhouettes and improved gait recognition accuracy through experiments using 56 subjects.
Communication Metrics for Software Development

We present empirical evidence that metrics on communication artifacts generated by groupware tools can be used to gain significant insight into the development process that produced them. We describe a test-bed for developing and testing communication metrics, a senior level software engineering project course at Carnegie Mellon University, in which we conducted several studies and experiments from 1991-1996 with more than 400 participants. Such a test-bed is an ideal environment for empirical software engineering, providing sufficient realism while allowing for controlled observation of important project parameters. We describe three proof-of-concept experiments to illustrate the value of communication metrics in software development projects. Finally, we propose a statistical framework based on structural equations for validating these communication metrics. Index Terms—Empirical software engineering, communication, statistics, structural equations. ——————————F—————————— 1I NTRODUCTION ETRICS applied to software artifacts have proven to be useful in measuring the impact of a tool or method in the context of a software project. In some cases, they enabled specific problems in the engineering processes to be identi- fied, thus demonstrating the value of metrics and other in- strumentation for process improvement. However, software code is only one of the many artifacts produced during soft- ware development. Moreover, it is often available only late in the process. The infrastructure and the resources needed to collect metrics on code are also non-negligible, and often prevents their use for identifying problems as they occur. Communication artifacts, such as electronic mail, memo- randa, or records generated by groupware tools, represent a different perspective on the development process. They are available throughout the project, they capture information about a more comprehensive set of artifacts (e.g., code, pro- cess, organization, politics, morale), and their form is inde- pendent of implementation technology, development infra- structure, or even the existence of a product. Metrics ap- plied to such communication artifacts can, therefore, pro- vide significant insight into the development process that produced them. In this paper, we discuss the design and evaluation of a set of communication metrics for software development. Our goal is to develop metrics that enable the assessment of a tool or a method in the context of a project. Our long-term goal is to provide metrics that help identifying problems as they occur. In Section 2, we illustrate possible uses of these metrics with an example.
Identification of genetic variants associated with maize flowering time using an extremely large multi-genetic background population.

Flowering time is one of the major adaptive traits in domestication of maize and an important selection criterion in breeding. To detect more maize flowering time variants we evaluated flowering time traits using an extremely large multi- genetic background population that contained more than 8000 lines under multiple Sino-United States environments. The population included two nested association mapping (NAM) panels and a natural association panel. Nearly 1 million single-nucleotide polymorphisms (SNPs) were used in the analyses. Through the parallel linkage analysis of the two NAM panels, both common and unique flowering time regions were detected. Genome wide, a total of 90 flowering time regions were identified. One-third of these regions were connected to traits associated with the environmental sensitivity of maize flowering time. The genome-wide association study of the three panels identified nearly 1000 flowering time-associated SNPs, mainly distributed around 220 candidate genes (within a distance of 1 Mb). Interestingly, two types of regions were significantly enriched for these associated SNPs - one was the candidate gene regions and the other was the approximately 5 kb regions away from the candidate genes. Moreover, the associated SNPs exhibited high accuracy for predicting flowering time.
Usual Interstitial Pneumonia and Non-Specific Interstitial Pneumonia: Serial Thin-Section CT Findings Correlated with Pulmonary Function

Objective We wanted to demonstrate and compare the serial high-resolution CTs (HRCT) and the pulmonary function test (PFT) findings of the usual interstitial pneumonia (UIP) and the non-specific interstitial pneumonia (NSIP). Materials and Methods The serial HRCT scans and the PFT results were retrospectively analysed and compared for 35 patients having UIP without significant honeycombing (UIP-w/o hc, < 5% of honeycombing at CT), 35 patients having UIP with honeycombing (UIP-w/i hc, ≥ 5% of honeycombing), and 25 patients with NSIP. The mortality rates were also compared. Follow-up CT scans were available in 75 patients (29 UIP-w/o hc patients, 22 UIP-w/i hc patients and 24 NSIP patients) and the follow-up periods ranged from 150 to 2,370 days. The initial and follow-up PFT data were available for 71 patients. Results On the initial CT, significant differences were present between the UIP-w/i hc patients and both the UIP-w/o hc patients and the NSIP patients in the overall extent, ground-glass opacity (GGO) away from the reticulation, reticulation and honeycombing (all p < 0.05). Improvement was noticed in five (17%) of 29 UIP-w/o hc patients, none of 22 UIP-w/i hc patients, and 9 (37%) of 24 NSIP patients; deterioration was noted in six (21%) UIP-w/o hc patients, two (9%) UIP-w/i hc patients and three (13%) NSIP patients (p = 0.044 between UIP-w/o and UIP-w/i hc; p = 0.637 between UIP-w/o hc and NSIP; p = 0.007 between UIP-w/i hc and NSIP). The serial changes of the pulmonary function in the NSIP patients were different from those noted for the UIP-w/i hc and UIP-w/o hc patients (p = 0.440 between UIP-w/o and UIP-w/i hc; p = 0.022 between UIP-w/o hc and NSIP; p = 0.003 between UIP-w/i hc and NSIP). Five (14%) of the 35 patients with UIP-w/o hc, 16 (46%) of the 35 patients with UIP-w/i hc and three (12%) of the 25 patients with NSIP died (p = 0.002, comparison for the three groups). Conclusion On CT, NSIP and UIP-w/o hc patients have similar patterns of parenchymal abnormalities and a similar likelihood of change in the extent of disease on follow-up. Patients with UIP-w/i hc have distinctive features and a worst prognosis.
Fitness mobile apps positively affect attitudes, perceived behavioral control and physical activities.

BACKGROUND Recent studies suggest that about 6 out of 10 users have installed a fitness tracking application on their smartphone. Nevertheless, more than 59% of adults do not engage in sufficient daily physical activity and much remains unknown with regard to the effectiveness of mobile applications. By adopting the Theory of Planned Behavior, we tested whether the use of fitness apps for daily steps tracking could positively influence people's health behavior. METHODS Participants (N.=78) were randomly assigned to one of two experimental conditions; in one condition, they were asked to adopt a fitness app for two weeks. No information regarding mobile apps was given for participants in the control condition. In order to test the effects of using a fitness app, a series of two-way mixed ANOVAs were conducted. RESULTS Participants in the experimental condition reported more favorable attitudes in the post-test compared to the pre-test, t(43)=4.09, P<0.001, d=0.65. By contrast, in the control condition, the difference on attitudes between pre-test and post-test was not significant (P=1.00). They also reported higher perceived behavioral control (PBC) scores, t(43) =4.97, P<0.001, d=0.75, whereas the difference on PBC for the control condition was not significant (P=0.27). Participants who used a fitness app reported to have walked more in the post-test compared to the pre-test, t(43) =2.41, P=0.02, d=0.36, whereas self-reported behavior did not change for participants in the control condition (P=0.46). CONCLUSIONS The present study provides encouraging evidence for the positive effects of using a fitness-tracking app in promoting health behavior.
Demographic Information Inference through Meta-Data Analysis of Wi-Fi Traffic

Privacy inference through meta-data (e.g., IP, Host) analysis of Wi-Fi traffic poses a potentially more serious threat to user privacy. First, it provides a more efficient and scalable approach to infer users’ sensitive information without checking the content of Wi-Fi traffic. Second, meta-data based demographics inference can work on both unencrypted and encrypted traffic (e.g., HTTPS traffic). In this study, we present a novel approach to infer user demographic information by exploiting the meta-data of Wi-Fi traffic. We develop an inference framework based on machine learning and evaluate its performance on a real-world dataset, which includes the Wi-Fi access of 28,158 users in five months. The framework extracts four kinds of features from real-world Wi-Fi traffic and applies a novel machine learning technique (XGBoost) to predict user demographics. Our analytical results show that, the overall accuracy of inferring gender and education level of users can be 82 and 78 percent, respectively. It is surprising to show that, even for HTTPS traffic, user demographics can still be predicted at accuracy of 69 and 76 percent, respectively, which well demonstrates the practicality of the proposed privacy inference scheme. Finally, we discuss and evaluate potential mitigation methods for such inference attacks.
The crystal chemistry of Si Al substitution in tourmaline

Thestructuresof ninegem-qualitycrystalsof V-bearing vite,a=15.95,c=7.17 A y= 1530 43,R3*,havebeenrefined to R indices of. -227o using graphite-monochromated MoKcl X-radiation; the crystals used for the X-ray dala collection were analyzed using an electron microprobe. The Si content of these crystals is significantly less than 6 atoms per formula unit; zrssignment of talAl sufficient to fill the Ji site results in a linear relationship between <Si-O> and t4lAI content. Examination of recent results of stucture refinement for tourmalile shows no well-defined relationship between 44> and constituent Lczf;:on radius. Conversely, there is a well-developed linear relationship between <I-O> and constifirent l-cation radius. Site-scattering refinement shows F to be strongly to completely ordered at the O(1) site. There is no significant positional disorder at the O(1) or O(2) sites.