Miracle-dz/UniFAR-FTUs huggingface dataset:
Determinants of Real-Time fMRI Neurofeedback Performance and Improvement – a Machine Learning Mega-Analysis

Real-time fMRI neurofeedback is an increasingly popular neuroimaging technique that allows an individual to gain control over his/her own brain signals, which can lead to improvements in behavior in healthy participants as well as to improvements of clinical symptoms in patient populations. However, a considerably large ratio of participants undergoing neurofeedback training do not learn to control their own brain signals and, consequently, do not benefit from neurofeedback interventions, which limits clinical efficacy of neurofeedback interventions. As neurofeedback success varies between studies and participants, it is important to identify factors that might influence neurofeedback success. Here, for the first time, we employed a big data machine learning approach to investigate the influence of 20 different design-specific (e.g. activity vs. connectivity feedback), region of interest-specific (e.g. cortical vs. subcortical) and subject-specific factors (e.g. age) on neurofeedback performance and improvement in 608 participants from 28 independent experiments. With a classification accuracy of 60% (considerably different from chance level), we identified two factors that significantly influenced neurofeedback performance: Both the inclusion of a pre-training no-feedback run before neurofeedback training and neurofeedback training of patients as compared to healthy participants were associated with better neurofeedback performance. The positive effect of pre-training no-feedback runs on neurofeedback performance might be due to the familiarization of participants with the neurofeedback setup and the mental imagery task before neurofeedback training runs. Better performance of patients as compared to healthy participants might be driven by higher motivation of patients, higher ranges for the regulation of dysfunctional brain signals, or a more extensive piloting of clinical experimental paradigms. Due to the large heterogeneity of our dataset, these findings likely generalize across neurofeedback studies, thus providing guidance for designing more efficient neurofeedback studies specifically for improving clinical neurofeedback-based interventions. To facilitate the development of data-driven recommendations for specific design details and subpopulations the field would benefit from stronger engagement in Open Science and data sharing.
Long-term Effects of Training Systems and Rootstocks on ‘McIntosh’ and ‘Honeycrisp’ Performance, a 15-year Study in a Northern Cold Climate—Part 1: Agronomic Analysis

Choice of cultivar, training system, planting density, and rootstock affect orchard performance and profitability. To provide guidance to growers in northern cold climates on these choices, a field trial was established in Peru, Clinton County, NY, in 2002, with two apple cultivars (Honeycrisp and McIntosh). From 2002 through 2016, we compared Central Leader on ‘M.M. 111’; Slender Pyramid on ‘M.26’ and ‘Geneva® 30’ (‘G.30’); Vertical Axis on ‘M.9 (Nic® 29)’ (‘M.9’), ‘Budagovsky 9’ (‘B.9’), and ‘G.16’; SolAxe on ‘M.9’, ‘B.9’, and ‘G.16’; and Tall Spindle on ‘M.9’, ‘B.9’, and ‘G.16’. Central Leader was planted at 539 trees/ha, Slender Pyramid at 1097 trees/ha, Vertical Axis and SolAxe at 1794 trees/ha, and Tall Spindle at 3230 trees/ha. Cumulative yield was higher with ‘McIntosh’ than with ‘Honeycrisp’. High planting densities (Tall Spindle) gave the highest cumulative yields (593 t·ha−1 on ‘McIntosh’ and 341 t·ha−1 on ‘Honeycrisp’). Tall Spindle (3230 trees/ha) on ‘M.9’ appeared to be the best option for ‘McIntosh’. On the other hand, for a weak-growing cultivar such as ‘Honeycrisp’, Tall Spindle on ‘B.9’ (366 t·ha−1) and Slender Pyramid (1097 trees/ha) on ‘G.30’ (354 t·ha−1) were the two combinations with the highest cumulative yield, largest fruit size (220–235 g), and greatest efficiency index (4.6–3.9 kg·cm−2).
Research on Intelligent Security Video Image Analysis Based on Deep Learning

For video surveillance analysis, target detection algorithms are particularly important. Aiming at the problem of target detection in road traffic scenes, this paper proposes a non-motor vehicle target detection method that uses EdgeBoxes algorithm and deep learning fusion. It is inspired by deep learning target classification algorithm Fast R-CNN, and combines non-motor vehicle data samples in VOC format to integrate road traffic scenes. We use the EdgeBoxes algorithm to extract the target of the sample. It is recommended to construct an appropriate amount of region of interest, and inputs the network for iterative training with the sample. In the target detection of road traffic scenes, compared with the traditional method based on the fusion of the basic EdgeBoxes algorithm and the optimized Fast R-CNN method, the detection accuracy is slightly improved, the calculation is significantly reduced, and the algorithm has advantages in time complexity.
Unveiling the sensory and interneuronal pathways of the neuroendocrine system in Drosophila

Neuroendocrine systems in animals maintain organismal homeostasis and regulate stress response. Although a great deal of work has been done on the neuropeptides and hormones that are released and act on target organs in the periphery, the synaptic inputs onto these neuroendocrine outputs in the brain are less well understood. Here, we use the transmission electron microscopy reconstruction of a whole central nervous system in the Drosophila larva to elucidate the sensory pathways and the interneurons that provide synaptic input to the neurosecretory cells projecting to the endocrine organs. Predicted by network modeling, we also identify a new carbon dioxide responsive network that acts on a specific set of neurosecretory cells and which include those expressing Corazonin (Crz) and Diuretic hormone 44 (DH44) neuropeptides. Our analysis reveals a neuronal network architecture for combinatorial action based on sensory and interneuronal pathways that converge onto distinct combinations of neuroendocrine outputs.
Identifikasi Bukti Digital pada Akuisisi Perangkat Mobile dari Aplikasi Pesan Instan “WhatsApp”

Aplikasi pesan instan menjadi salah satu alasan utama untuk seorang pengguna menggunakan internet. Saat ini WhatsApp menjadi aplikasi pesan instan dengan pengguna terbesar di indonesia karena beragam fitur yang telah didukung. Hal ini tentu saja membuat WhatsApp bukan hanya digunakan untuk bertukar informasi biasa tapi juga informasi terkait kasus kejahatan. Sehingga bukti digital aplikasi pesan instan WhatsApp pada smartphone menjadi potensial dalam berbagai kasus kriminal dan proses persidangan. Pada penelitian ini dilakukan analisis terhadap bukti digital whatsapp yang dapat diperoleh dalam proses akuisisi perangkat smartphone. Target perangkat yang diakuisisi pada penelitian ini adalah smartphone berbasis android dan iOS. Hasil ekstraksi didapatkan beberapa bukti digital aplikasi WhatsApp yang berhasil didapatkan meskipun perangkat tidak dilakukan proses root/jailbreak terlebih dahulu.
Effects of Guanidinoacetic acid supplements on laying performance, egg quality, liver nitric oxide and energy metabolism in laying hens at the late stage of production

Abstract The objective was to elucidate the effects of dietary supplementation with guanidinoacetic acid (GAA) on performance, egg quality and the liver antioxidant activity of laying hens. A total of 128, 72-week-old ISA Brown laying hens were randomly divided into four equal groups (32 birds), and each subgroup had eight replicates (four birds/cage). The control group (GAA0) fed the basal diet with no supplements, while the other experimental groups fed the basal diets supplemented with 0.5 (GAA1), 1.0 (GAA2) and 1.5 (GAA3) g of GAA/kg diet. The experiment lasted for 6 weeks. The addition of GAA at a rate of 1.5 g kg−1 significantly increased the hen-day egg production and egg mass as compared to the control group (P = 0.016 and 0.003, respectively). Although the egg weight was not affected (P = 0.521) by the dietary supplements, the shell ratio, shell thickness, yolk index and Haugh units increased linearly with the increase in the dietary supplements of the GAA (P = 0.036, 0.001, 0.012 and 0.004, respectively). The liver MDA levels decreased linearly with the increment in the dietary levels of the GAA (P = 0.012). Birds in the GAA2 and GAA3 showed a significantly higher liver nitric oxide level (52.50 and 54.21 mg/g, respectively) when compared with GAA0 and GAA1 groups (P = 0.029). Compared to the GAA0 group, all GAA-supplemented groups showed significantly higher liver ATP levels (P = 0.047). In conclusion, the dietary GA supplements at doses of 1.0 or 1.5 g kg−1 may improve the laying performance, antioxidant activity and the status of cellular energy metabolism in laying hens.
Non-invasive ultrasound quantification of Scar Tissue Volume predicts functional changes during tendon healing

Tendon injuries are very common and disrupt the transmission of forces from muscle to bone, leading to impaired function and quality of life. Successful restoration of tendon function after injury is a challenging clinical problem due to the pathological, scar-mediated manner in which tendons heal. Currently, there are no standard treatments to modulate scar tissue formation and improve tendon healing. A major limitation to the identification of therapeutic candidates has been the reliance on terminal end-point metrics of healing in pre-clinical studies, which require a large number of animals and result in destruction of the tissue. To address this limitation, we have identified quantification of Scar Tissue Volume (STV) from ultrasound imaging as a longitudinal, non-invasive metric of tendon healing. STV was strongly correlated with established endpoint metrics of gliding function including Gliding Resistance (GR) and Metatarsophalangeal (MTP) Flexion Angle. However, no associations were observed between STV and tensile mechanical properties. To define the sensitivity of STV to identify differences between functionally discrete tendon healing phenotypes, we utilized S100a4 haploinsufficient mice (S100a4GFP/+), which heal with improved gliding function relative to wildtype (WT) littermates. A significant decrease in STV was observed in S100a4GFP/+repairs, relative to WT at day 14. Taken together, these data suggest US quantification of STV as a means to facilitate the rapid screening of biological and pharmacological interventions to improve tendon healing, and identify promising therapeutic targets, in an efficient, cost-effective manner.
The Changes of Media Landscape in Malaysia: How Citizen Journalism Poses Threats to Traditional Media

The rise of the Internet and social media have provided alternative ways for people to access information. Communication technologies have given a new platform for ordinary people outside of the journalism profession to become content creators instead of content users. This gives rise to citizen journalism as ordinary people can publish, share, discuss and debate about news and stories in a global sphere with others. While some might view this trend as a positive way of disseminating information, citizen journalism is facing numerous criticism as people are questioning their credibility regarding the news sources and the ethical code of practice that they use when collecting information. This study aims to highlight the changes taking place in the Malaysian media landscape in response to citizen journalism as well as the threats towards mainstream journalism. Data was collected through a qualitative in-depth interview method with five journalists working in the mainstream news organizations in Malaysia. All respondents have vast experience in journalism, both in the traditional newsroom and online news portal settings. The results indicated that changes occurring in the media landscape are due to several reasons namely instant gratification of the news; changed mode of transmission; new styles of news writing; open and freer media environment and change of gatekeeping process. Threats posed by citizen journalism to traditional media are commercial impact, stealing of credits and stiff competition. It was concluded that newsrooms and journalists have to change in order to face the challenges posed by citizen journalism.
Results of special types for subclasses of analytic functions

Abstract A subclass of normalized analytic functions symmetric with respect to points is introduced. The second, the third and the fourth coefficients bounds are obtained. The Fekete-Szego inequality for a univalent normalized functions f in the subclass is obtained and Hankal determinant inequalities are estimated. The solution Is given for some values of a constant for the differential equation
Detection of Coordinate Based Accident-Prone Areas on Road Surface using Machine Learning Methods

The growth in the road networks in India and other developing countries have influenced the growth in transport industry and other industries, which depends on the road network for operations. The industries such as postal services or mover services have influenced the similar growths in these industries as well. However, the dependency of these industries is high on the road surface conditions and any deviation on the road surface conditions can also influence the performance of the services provided by the mentioned services. Nonetheless, the conditions of the road surface are one of the prime factors for road safety and number of evidences are found, which are discussed in subsequent sections of this work, that the bad road surface conditions are increasing the road accidents. Several parallel research attempts are deployed in order to find out, the regions where the road surface conditions are not proper, and the traffic density is higher. Nevertheless, outcomes of these parallel works are highly criticised due to the lack of accuracy in detection of the road surface defects, detection of accurate location of the defects and detection of the traffic density data from various sources. Thus, this work proposes a novel framework for detection of the road defect and further mapping to the spatial data coordinates resulting into the detection of the accident-prone zones or accident affinities of the roads. This work deploys a self-adjusting parametric coefficient-based regression model for detection of the risk factors of the road defects and in the other hand, extracts the traffic density of the road regions and further maps the accident affinities. This work outcomes into 97.69% accurate detection of the road accident affinity and demonstrates less complexity compared with the other parallel research outcomes
The influence of early feeding on intestinal development and performance of broiler chickens

In the first days after hatch, the development of organs such as the gastrointestinal tract, and the growth performance may be affected by the time in between hatch and first feed intake. In current practice, time between hatch and moment of first feed intake may take long time because of variation in hatch time, chick handling, and transportation time. Feed deprivation, especially during the first days after hatch, depresses intestinal development on the short and long term, reflected by a lower intestinal weight, shorter length, lower enzymatic activity, altered villi and crypt cell density, and lower crypt depths and villi heights and finally, depressed growth. The objective of this study was to investigate effects of the moment of first feed intake after hatch on intestinal development and growth performance of broiler chickens. A total 60 unsexed day-old Lohmann broiler chicks were randomly assigned into 3 treatments of 20 chicks each in four replicates (5 chicks each). The treatments were time first feed and water access after hatch, including 12, 42 and 72 hours. Body weight gain and feed intake were recorded weekly and the intestinal development were sampled at 12 days for the measurement of ileum histology and length of gastrointestinal tract. Results obtained were as follows: Time between hatch and moment of first feed intake had no significant effect (P> 0.05) on width of the villi. However, the height of villi, depth of the crypt dan length of the gastrointestinal tract were significantly affected by treatment. The longer delay in the provision of feed and water in day-old chick were lower height of villi and depth of the crypt, dan shorter length of the gastrointestinal tract. Statistically, performance parameters had any difference among treatments, except for feed conversion. The final body weight and feed intake decreased with increasing time between hatch and moment of first feed intake. The results suggest that early delivery of first feed can influence development and growth of gastrointestinal tract. It is also beneficial to improve posthatch growth performance of broiler chickens.
Étude des liens entre la texture et les propriétés de diffusion de molécules modèles dans des milieux poreux bimodaux

Nous avons cherche a etablir un lien entre le transport de molecules sondes dans des catalyseurs bimodaux d'hydrotraitement et les parametres texturaux de ces milieux poreux. Les coefficients de diffusion des molecules ont ete mesures dans les macropores et dans les domaines mesoporeux par RMN a gradient de champ pulse, deux regimes de diffusion ont ete mis en evidence. Les isothermes d'adsorption non lineaire ont ete mesurees. Deux modeles de diffusion-adsorption ont ete construits en utilisant la theorie du changement d'echelle : un modele a simulation directe et un modele equilibre local. L'ajustement des courbes simulees aux courbes experimentales de cinetique de diffusion en colonne permet de determiner les parametres d'adsorption et le coefficient de diffusion effectif dans le domaine mesoporeux. Ces parametres sont en accord avec les mesures RMN et les isothermes. Nous avons montre que ces systemes avaient le meme comportement qu’un milieu homogene. ABSTACT : The aim of this work is to understand the link between transport properties of large probe molecules and the texture of biporous (meso and macroporous) catalysts. Diffusion coefficients in porous media are measured by pulsed field gradient NMR. This technique allows us to determine two diffusion coefficients: one in the macroporosity and another in the mesoporosity. Two models are built by using a volume averaging technique : a direct simulation model and a local equilibrium model. The non linear adsorption isotherms of probe molecules are measured. Simulations are compared with experimental data obtained by measuring the decrease of the concentration of probe molecules in a solution in contact with a biporous support. The obtained effective diffusion coefficient in the mesoporous phase and the adsorption parameters are in good agreement with previous NMR and isotherms measurements. We show that this kind of system behaves as a homogeneous medium
Analysis for predicting the prevalence and risk factors of peri-implantitis

Background: Peri-implant disease at functional osseointegrated implants comprises of pathologies of infectious nature: peri-implant mucositis, and peri-implantitis. Hence; the present study was undertaken for predicting the prevalence and risk factors of peri-implantitis. Materials & methods: A total of 239 patients who underwent dental implants procedure for missing maxillary first permanent molars were included in the presents study. Complete demographic and clinical details of all the patients were obtained. All the dental implant procedures were carried out under local anaesthesia under proper septic conditions. Follow-up was done in all the patients and both clinical and radiographic examination was carried out. Prevalence of peri-implantitis and its various risk factors were evaluated. Results: Prevalence of peri-implantitis was found to be 8.36 percent (20 patients out of 239 patients). Smoking habit was found to be present in 75 percent of the patients with peri-implantitis. 70 percent of the patients with peri-implantitis were diabetic. Fully acid etched dental implant surface was present in 55 percent of the patients with peri-implantitis. Conclusion: Peri-implantitis is not a prevalent complication of dental implant therapy. Also, apart from diabetes and smoking, no other true risk factor of peri-implantitis could be established from above results.
Studies on the interaction of a single domain of protein G from streptococcus with human Fc and Fab

Protein G (SpG) is a Type III bacterial Fc receptor that binds selectively and non-antigenically to both the Fc and Fab regions of IgG. Here studies are described aimed at understanding the individual contributions to complex stability made by amino acid residues known to make contacts with either the Fab or Fc. Specific amino-acid residues that contribute to these binding interactions via a network of hydrogen bonds have been identified and studied by a programme of site directed mutagenesis. Unique tryptophan residues (W42 or W14) have been used to facilitate equilibrium and pre-equilibrium fluorescence studies to observe binding to Fc or Fab and to determine the Kd for the various equilibria. The effect of secondary substitutions of residues implicated in bond formation to either the Fc or Fab IgG fragment have been determined in order to generate SpG domains with a range of binding affinities for biotechnological uses. SpG species that only bind to Fc or Fab have also been developed. The mutant W42F has been shown by ITC studies to have lost the ability to bind to Fc, and the double mutant T15A-T16A shows no detectable binding to Fab. ITC and kinetic studies at various temperatures have been employed to characterise the thermodynamic parameters underlying binding of wild type or mutated SpG to Fc or Fab. Some restoration of Fc binding activity has been brought about by the placement of a tryptophan at residue 14 (E14W), which may be a useful protein for affinity chromatographic applications as a Kd in the micromolar range is ideal for affinity ligands where easy elution of the bound target protein is required. A dramatic reduction in the affinity of SpG for Fc has been obtained for the E26A mutation, and the N34 residue has been found to be significant in Fc binding, with a 50-fold decrease in affinity for the N34A mutation. The electrostatic nature of the interactions and their sensitivity to changes in pH has also been studied and results showed that Q31E has increased Kd by approximately 6-fold, demonstrating that a negative charge at this position is detrimental to binding. The lower affinity and the influence from the ionisable group would offer advantages for the elution of the Ig from the column.
Spread of Two Invasive Flies (Diptera: Drosophilidae) Infesting Commercial Fruits in Southeastern Brazil

Summary Two invasive fruit flies, Drosophila suzukii Matsumura and Zaprionus indianus Gupta (Diptera: Drosophilidae), recently have become established, and are expanding their range in the Neotropics. This research documents the range expansion of these species in southeastern Brazil, where they were found infesting cultivated blackberries and strawberries in the highlands of Espírito Santo, Brazil. Drosophila suzukii also was found associated with rotting Psidium cattleianum, and for the first time associated with papaya at sea level. Drosophila suzukii and Z. indianus may further affect establishment and production of important soft fruit crops and papaya in this region of Brazil. Management methods for fruit production in this Brazilian region need to be improved to avoid damage and further spread of D. suzukii.