Miracle-dz/UniFAR-FTUs huggingface dataset:
on anterior posterior during memory for complex scenes.

Objectives: Hippocampal dysfunction has been proposed as a mechanism for memory de ﬁ cits in schizophrenia. Availableevidencesuggeststhattheanteriorandposteriorhippocampuscouldbedifferentiallyaffected.Accord-ingly,weusedfMRItotestthehypothesisthatactivityinposteriorhippocampusisdisproportionatelyreducedin schizophrenia, particularly during spatial memory retrieval. Methods: 26 healthyparticipants and 24 patients with schizophrenia from the UCDavis EarlyPsychosis Program werestudiedwhilefMRIwasacquiredona3TeslaSiemensscanner.Duringencoding,participantswereoriented tocriticalitems throughquestionsabout itemfeatures(e.g., “ Doesthelamphavea square shade? ” ) orspatial lo- cation (e.g., “ Is the lampon the tablenextto the couch? ” ). At test, participants determined whether scenes were changed or unchanged. fMRI analyses contrasted activation in a priori regions of interest (ROI) in anterior and posterior hippocampus during correct recognition of item changes and spatial changes. Results: As predicted, patients with schizophrenia exhibited reduced activation in the posterior hippocampus during detection of spatial changes but not during detection of item changes. Unexpectedly, patients exhibited increased activation of anterior hippocampus during detection of item changes. Whole brain analyses revealed reduced fronto-parietal and striatal activation in patients for spatial but not for item change trials. Conclusions: Results suggest a gradient of hippocampal dysfunction in which posterior hippocampus – which is necessary for processing ﬁ ne-grained spatial relationships – is underactive, and anterior hippocampus – which may process context more globally - is overactive.
Stronger and Faster Wasserstein Adversarial Attacks

Deep models, while being extremely flexible and accurate, are surprisingly vulnerable to "small, imperceptible" perturbations known as adversarial attacks. While the majority of existing attacks focus on measuring perturbations under the $\ell_p$ metric, Wasserstein distance, which takes geometry in pixel space into account, has long been known to be a suitable metric for measuring image quality and has recently risen as a compelling alternative to the $\ell_p$ metric in adversarial attacks. However, constructing an effective attack under the Wasserstein metric is computationally much more challenging and calls for better optimization algorithms. We address this gap in two ways: (a) we develop an exact yet efficient projection operator to enable a stronger projected gradient attack; (b) we show that the Frank-Wolfe method equipped with a suitable linear minimization oracle works extremely fast under Wasserstein constraints. Our algorithms not only converge faster but also generate much stronger attacks. For instance, we decrease the accuracy of a residual network on CIFAR-10 to $3.4\%$ within a Wasserstein perturbation ball of radius $0.005$, in contrast to $65.6\%$ using the previous Wasserstein attack based on an \emph{approximate} projection operator. Furthermore, employing our stronger attacks in adversarial training significantly improves the robustness of adversarially trained models.
Necessity for More Realistic Contact Simulation

—Given the recent progress in large-scale data-driven methods, sim-to-real is quickly becoming an enabler for access to machine learning research, alleviating hardware costs and physical constraints. Simulation’s role in validating new methods is unlikely to diminish. While success in simulation is far from a guarantee of success in the real world, it serves as a valuable baseline and sanity check during development. In addition, mission-critical tasks with high costs and strict time constraints, such as deep sea and space missions, rely on simulation to determine the minimum plausibility of the system. As visual simulation matures and visual perception’s limits are acknowledged in the manipulation community, tactile perception is gaining steady interest. Unlike visual simulation, which relies less on physics than on rendering, contact simulation depends largely on the ﬁdelity of physics modeling, which is crucial for interaction-heavy tasks like manipulation and locomotion. At the present, contact simulation is primitive even for rigid bodies, not to mention soft and deformable bodies. This presents a severe lack of minimum baseline and accessibility, especially given the limited availability and ﬂakiness of cutting-edge contact sensors. Any improved contact simulation is a prerequisite, before sim-to-real transfer can even come into relevance in contact perception. This position paper supports this view by summarizing the state of the art, challenges, and the latest progress as cursors forward.
Gastroparesis on Diabetes Mellitus Patients

Diabetes mellitus is a metabolic disease of multiple etiologies. Global statistics of diabetes mellitus showed that 382 million people in the world had the disease; type II diabetes mellitus represented 90% of cases. Diabetic gastroparesis is a serious complication due to diabetes mellitus. Further studies suggest that diabetes mellitus is associated with up to 75% of gastrointestinal symptoms, in diabetic gastroparesis; the antral body contractions are ineffective, although the smooth muscle layers appear to be normal. Gastric emptying scintigraphy is considered the gold standard for diagnosis and quantification of delayed gastric emptying. The goal of treatment is to reduce symptoms, correct nutrition, and improve quality of life. Includes prokinetic medications like first line, nausea and vomiting can be controlled with some antiemetic medications, it should also include education and support diet, behavior changes.
Adapting to Drifting Preferences in Recommendation

Machine learning is often used to acquire knowledge in domains that undergo frequent changes, such as networks, social media, or commercial markets. These frequent changes pose a challenge to most machine learning methods as they have difﬁculty adapting. In this paper, we consider a forum content recommender system for massive open online courses (MOOCs) as an example where recommendations have to adapt to new items and evolving user preferences. We formalize the recommendation problem as a sequence prediction problem and compare different recommendation methods, including a new method called context tree (CT), which can be efﬁciently learned and applied to online sequential recommendation task. The results show that the CT recommender performs better than other methods because of better adaptation to changes in the domain.
Evaluation of biological response modification and immunotherapeutic activities of barley-derived arabinoxylans against coccidiosis in commercial broilers

Plant-derived polysaccharides have been reported for diverse biological response modification (BRM) and immunotherapeutic (IT) activities in animals by activating their defense systems to perform better immunogenically against invading pathogens. Keeping this in view, this study was conducted to assess the BRM and IT activities of barley ( Hordeum vulgare L.)-derived arabinoxylans (AXs) against coccidiosis in broilers. Significantly enhanced (P < 0.05) in vivo and in vitro lymphoproliferative responses to T-cell mitogens were revealed in broilers administered barley AXs when compared to the control group. Humoral immune response in terms of antibody titers against sheep erythrocytes was also found higher (P < 0.05) in AX-administered chickens. Furthermore, AX-administered chickens also showed higher weekly weight gains and improved feed conversion ratios as compared to controls. Results of the challenge experiment showed that the percentage of protection and daily weight gains were statistically higher (P < 0.05) whereas mean oocysts per gram of droppings and lesion scores were significantly lower (P < 0.05) in the chickens administered barley AXs as compared to controls. In conclusion, barley-derived AXs led to better growth performance and elicited humoral and cellular immune responses in commercial broilers that persisted against coccidial infection in broiler chickens.
An Adaptive Metric for BRDF Appearance Matching

Image-based BRDF matching is a special case of inverse rendering, where the parameters of a BRDF model are optimized based on a photograph of a homogeneous material under natural lighting. Using a perceptual image metric, directly optimizing the difference between a rendering and a reference image can provide a close visual match between the model and reference material. However, perceptual image metrics rely on image-features and thus require full resolution renderings that can be costly to produce especially when embedded in an non-linear search procedure for the optimal BRDF parameters. Using a pixel-based metric, such as the square difference, can approximate the image error from a small subset of pixel. Unfortunately, pixel-based metrics are often a poor approximation of human perception of the material’s appearance. We show that comparable quality results to a perceptual metric can be obtained using an adaptive pixel-based metric that is optimized based on the appearance similarity of the material. As the core of our adaptive metric is pixel-based, our method is amendable to image-subsampling, thereby greatly reducing the computational cost.
Characterisation of the 3D Paper Structure with X-ray Synchrotron Radiation Microtomography

Paper is a complex three-dimensional network of fibres, pores and often fillers. The main goal of this study is to characterise its structure in a non invasive and non destructive way. In order to overcome the limitations of 2D measurements, Synchrotron Radiation microtomography is used to visualise the samples. Coupled with appropriate processing tools, it allows a quantifica- tion of some structural characteristics on the samples. This is the main aim of this paper. Different articles relate the feasibility of such a study for paper samples: imaging at the European Synchrotron Radiation Facility (ESRF, France) in phase contrast [1] or in absorption mode [2] gives the opportunity to reach a pixel size smaller than a micron which can not be obtained with classical tomographs [3]. A first step is to visualise the structure then, structural parameters are extracted from these 3D data [4]. However, this requires a segmentation technique adapted for application to typical paper samples that are constituted of three phases. The first step consists in the segmentation of the different phases, namely, air, fibres and fillers. The amount of each component may be evaluated. This was validated for both the porosity and the filler content. Furthermore, structural parameters were calculated from the binarised volumes. The comparison with the published results validates the calculation.
Average-case analysis of programs: Automated recurrence analysis for almost-linear bounds

We consider the problem of developing automated techniques to aid the average-case complexity analysis of programs. Several classical textbook algorithms have quite efﬁcient average-case complexity, whereas the corresponding worst-case bounds are either inefﬁcient (e.g., Q UICK -S ORT ), or completely ineffective (e.g., C OUPON - C OLLECTOR ). Since the main focus of average-case analysis is to obtain efﬁcient bounds, we consider bounds that are either logarithmic, linear, or almost-linear ( O (log n ) , O ( n ) , O ( n · log n ) , respectively, where n represents the size of the input). Our main contribution is a sound approach for deriving such average-case bounds for randomized recursive programs. Our approach is efﬁ-cient (a simple linear-time algorithm), and it is based on (a) the analysis of recurrence relations induced by randomized algorithms, and (b) a guess-and-check technique. Our approach can infer the asymptotically optimal average-case bounds for classical randomized algorithms, including R ANDOMIZED -S EARCH , Q UICK - S ORT , Q UICK -S ELECT , C OUPON -C OLLECTOR , where the worst-case bounds are either inefﬁcient (such as linear as compared to logarithmic of average-case, or quadratic as compared to linear or almost-linear of average-case), or ineffective. We have implemented our approach, and the experimental results show that we obtain the bounds efﬁciently for various classical algorithms.
Semismooth Newton Algorithm for Efficient Projections onto ℓ1, ∞-norm Ball

The structured sparsity-inducing (cid:96) 1 , ∞ -norm, as a generalization of the classical (cid:96) 1 -norm, plays an important role in jointly sparse models which select or remove simultaneously all the variables forming a group. However, its resulting problem is more difﬁcult to solve than the conventional (cid:96) 1 -norm constrained problem. In this paper, we propose an efﬁcient algorithm for Euclidean projection onto (cid:96) 1 , ∞ -norm ball. We tackle the projection problem via semismooth Newton al-gorithm to solve the system of semismooth equations. Meanwhile, exploiting the structure of the Jacobian matrix via LU decomposition yields an equivalent algorithm which is proved to terminate after a ﬁnite number of iterations. Empirical studies demonstrate that our proposed algorithm outperforms the existing state-of-the-art solver and is promising for the optimization of learning problems with the (cid:96) 1 , ∞ -norm ball constraint.
Manifold Identification for Ultimately Communication-Efficient Distributed Optimization

This work proposes a progressive manifold iden-tiﬁcation approach for distributed optimization with sound theoretical justiﬁcations to greatly reduce both the rounds of communication and the bytes communicated per round for partly-smooth regularized problems such as the (cid:96) 1 - and group-LASSO-regularized ones. Our two-stage method ﬁrst uses an inexact proximal quasi-Newton method to iteratively identify a sequence of low-dimensional manifolds in which the ﬁnal solution would lie, and restricts the model update within the current manifold to gradually lower the order of the per-round communication cost from the problem dimension to the dimension of the manifold that contains a solution and makes the problem within it smooth. After identifying this manifold, we take superlinear-convergent truncated semismooth Newton steps computed by pre-conditioned conjugate gradient to largely reduce the communication rounds by improving the convergence rate from the existing linear or sublinear ones to a superlinear rate. Experiments show that our method can be orders of magnitudes lower in the communication cost and an order of magnitude faster in the running time than the state of the art.
Assessment of the Influence of Aqueous Allium sativum Bulb (Garlic) Extract on Testicular Activity in Wistar Albino Rats

Garlic is a widely consumed medicinal plant and most of its biological effects have been established. But its effect on reproductive function and fertility in males is not conclusively studied. This study was conducted to investigate the influence of aqueous extract of garlic bulb on sperm characteristics and serum reproductive hormone concentrations in Wistar albino rats. Animals were grouped randomly (n=5/group) and gavaged with garlic extract (0, 50, 100, 200 or 300 mg/kg/day) for 28 days. Some other groups received garlic extract 24 h after they were injected alloxan (100 mg/kg, ip). Animals were sacrificed and serum levels of FSH, LH and testosterone were analysed as well as sperm collected from the epididymis. Sperm morphology, FSH and LH were not affected in all rats that received only garlic extract compared to control. In addition, sperm motility, sperm count and testosterone were reduced (P < 0.05) in rats that received 300 mg/kg extract, but the lower dose treatments failed to produce any significant effect. In alloxan+extract administered rats, sperm motility and count were reduced dose-dependently, but effect on sperm count was significant only in rats that received 200 and 300 mg/kg of extract. Furthermore, testosterone level was decreased, while the other hormones were unaltered. The results suggest that garlic alters sperm characteristics and decreases testosterone concentration in rats when chronically consumed at high doses.
The Impact of the Customs Union Agreement on GCC Bilateral Trade, using Aggregated and Disaggregated Data

This paper studies different aspects of trade integration among Gulf Cooperation Council (GCC) member countries by examining the effect of the GCC Customs Union (GCC CU) on trade in the region during 1995-2012 period. Different forms and specifications of the gravity model of international trade are applied to a set of bilateral trade flows among 38 countries representing GCC countries and their major trade partners during the 1995-2012 period. By investigating the effect of the GCC CU on aggregate and disaggregate trade, the findings of this paper have interesting implications. The use of disaggregated trade data is important in investigating the GCC CU, since the aggregate results may suffer from aggregation bias. In addition, it helps identify the sectors that benefit more from GCC CU, which is an important issue for GCC countries that seek the integration of their economies. The results of the disaggregated trade analysis suggest that the value added or advantage of GCC CU trade creation was more concentrated in sectors that exhibit lower shares of GCC intra-trade during 1995-2012.
Conﬁgurable consistency WPE

Geo-replicated data stores are increasingly important for the internet infrastructure. In order to facilitate application development on top of these data stores, consistency notions are used as contracts between the developer and the data store. These consistency notions are often too strict, leading to poor performance, or too weak, leading to unpredictable behaviors. This has led to a recent emergence of hybrid consistency notions that can be conﬁgured according to application requirements. These conﬁgurable consistency notions come with ranging support to help users conﬁgure them depending on their application requirements. In this report I survey three diﬀerent conﬁgurable consistency notions together with the developer support that they provide for conﬁguring them. The diﬀerent notions are compared in terms of expressiveness, implementability, and ease of conﬁgurability. Finally, I will propose possible directions for future work in this domain.
Barriers to the Political Empowerment of Women in Dir Lower

Women’s political participation in Malakand Division in general and Dir Lower in particular confronts a number of social, cultural, economic, political and religious barriers which hinder their empowerment. This study investigates various barriers to the political empowerment of women in Dir Lower. Main aim of the research work is to identify the various social, economic, political, religious and cultural factors and barriers which deprive women from participation in the political activities. The study has been conducted in four tehsils i.e. Balambat, Timargara, Khall and Maidan of District Dir Lower in Khyber Pakhtunkhwa. Data for the study was obtained through semi structured interviews and focused group discussions with political leaders, elected representatives, female councilors, village elders, male and female students and female folk of the area. The data reveals that there exist various barriers in the form of patriarchy, orthodox attitudes of the people, talibanization, lack of education, misinterpretation and wrong practice of Pakhtunwali and Seclusion (Purdah) etc. towards the political participation and political empowerment of women. Introduction At the time of independence in 1947, Dir was a state ruled by Nawab Shah Jehan Khan. It was merged in Pakistan in 1969 and later on declared a district in 1970. In 1996, the district was divided into two, with Upper and Lower Dir forming two separate district respectively. District Lower Dir is located in the north-western part of Khyber Pakhtunkhwa province and is spread over an area of 1583 square kilometers. Apart from small areas in the south-west, the District is mostly a rugged mountainous terrain. The District borders with swat District on its East, Afghanistan on its West, Upper Dir and Chitral on its North & north-west respectively and Malakand & Bajaur Agency on its South. The district is represented in the Provincial assembly by four elected MPA’s and in the National Assembly by one MNA. Although women in large number are exercising their rights and duties within the fold of Islam in Dir Lower, however their participation in political activities is almost nil. In Dir, which is considered as one of the most socially conservation region, politics is considered as a men-only affair. Since the merger of the princely state of Dir with Pakistan in 1969, there have been 10 general elections in the, but women were never allowed either to actively participate in politics or vote. However it was in May, 2013 that in an unprecedented development, all political and religious parties of Dir Lower district of Khyber Pakhtunkhwa expressed willingness to allow
School Violence Prevention: Teachers Establishing Relationships With Students Using Counseling Strategies

Although youth violence rates continue to decrease in the United States, it remains the second leading cause of death for adolescents. Furthermore, school violence remains a sociocultural concern, especially due to increasing media attention. Research consistently indicates that preventing school violence involves measures that go beyond formal protocols. One factor that has emerged from this research is that the quality of relationships between students and teachers, commonly referred to as school connectedness, may have a significant role in preventing school violence. However, there is very little literature that addresses how mental health professionals, such as school counselors, can assist teachers in fostering school connectedness with their students. This article provides a theoretical conceptualization of teacher–student relationship and communication skills that contribute to eventual school violence prevention through the development of school connectedness. The ultimate goal of this theoretical model is to provide conceptual and applied guidance in bridging the gap between research and practice.
Complex Skill Acquisition through Simple Skill Adversarial Imitation Learning

Humans are able to think of complex tasks as combinations of simpler subtasks in order to learn the complex tasks more efficiently. For example, a backflip could be considered a combination of four subskills: jumping, tucking knees, rolling backwards, and thrusting arms downwards. Motivated by this line of reasoning, we propose a new algorithm that trains neural network policies on simple, easy-to-learn skills in order to cultivate latent spaces that accelerate adversarial imitation learning of complex, hard-to-learn skills. We evaluate our algorithm on a difficult task in a high-dimensional environment and see that it consistently outperforms a state-of-the-art baseline in training speed and overall task performance.
THE EFFECTIVENESS OF USING RECYCLED CONCRETE IN CONSTRUCTION PROJECTS-MECHANICAL PROPERTIES INVESTIGATION

Green concrete has always been a revolutionary subject in the concrete industry history. In general, concrete is a friendly environmental material because of its narrow overall impact (per ton) on the environment. This paper introduces the “green” concrete as the using alternative and/or recycled waste materials (such as fly ash and recycled concrete aggregates) in the concrete production process in order to reduce environmental impact, energy spending, and natural resource use. This paper also covers the main aspects of using and choosing adequate materials for green concrete.