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Peer review is the backbone of academia and humans constitute a cornerstone of this process, being responsible for reviewing submissions and making the final acceptance/rejection decisions. Given that human decision-making is known to be susceptible to various cognitive biases, it is important to understand which (if any) biases are present in the peer-review process, and design the pipeline such that the impact of these biases is minimized. In this work, we focus on the dynamics of discussions between reviewers and investigate the presence of herding behaviour therein. Specifically, we aim to understand whether reviewers and discussion chairs get disproportionately influenced by the first argument presented in the discussion when (in case of reviewers) they form an independent opinion about the paper before discussing it with others. In conjunction with the review process of a large, top tier machine learning conference, we design and execute a randomized controlled trial that involves 1,544 papers and 2,797 reviewers with the goal of testing for the conditional causal effect of the discussion initiator's opinion on the outcome of a paper. Our experiment reveals no evidence of herding in peer-review discussions. This observation is in contrast with past work that has documented an undue influence of the first piece of information on the final decision (e.g., anchoring effect) and analyzed herding behaviour in other applications (e.g., financial markets). Regarding policy implications, the absence of the herding effect suggests that the current status quo of the absence of a unified policy towards discussion initiation does not result in an increased arbitrariness of the resulting decisions.

Quantifying differences or similarities in connectomes has been a challenge due to the immense complexity of global brain networks. Here we introduce a noninvasive method that uses diffusion MRI to characterize whole-brain white matter architecture as a single local connectome fingerprint that allows for a direct comparison between structural connectomes. In four independently acquired data sets with repeated scans (total N = 213), we show that the local connectome fingerprint is highly specific to an individual, allowing for an accurate self-versus-others classification that achieved 100% accuracy across 17,398 identification tests. The estimated classification error was approximately one thousand times smaller than fingerprints derived from diffusivity-based measures or region-to-region connectivity patterns for repeat scans acquired within 3 months. The local connectome fingerprint also revealed neuroplasticity within an individual reflected as a decreasing trend in self-similarity across time, whereas this change was not observed in the diffusivity measures. Moreover, the local connectome fingerprint can be used as a phenotypic marker, revealing 12.51% similarity between monozygotic twins, 5.14% between dizygotic twins, and 4.51% between none-twin siblings, relative to differences between unrelated subjects. This novel approach opens a new door for probing the influence of pathological, genetic, social, or environmental factors on the unique configuration of the human connectome.

Why did the volatility of U.S. real GDP decline by more than the volatility of final sales with the Great Moderation in the mid-1980s? One explanation is that firms shifted their inventory behavior toward a greater emphasis on production smoothing. We investigate the role of inventories in the Great Moderation by estimating an unobserved components model that identifies inventory and sales shocks and their propagation in the aggregate data. Our estimates provide no support for increased production smoothing. Instead, smaller transitory inventory shocks are responsible for the excess volatility reduction in output compared to sales. These shocks behave like informational errors related to production that must be set in advance and their reduction also helps explain the changed forecasting role of inventories since the mid-1980s. Our findings provide an optimistic prognosis for a continuation of the Great Moderation, despite the dramatic movements in output during the recent economic crisis.

The most frequent neurodegenerative illness among senior people and the main cause of dementia is Alzheimer's disease. The present dementia medications available only help with the symptoms of cognitive deficits and have several negative effects. The current study's goal is to assess the effects of curcumin and coenzyme Q10, two herbal medicines, both separately and in combination, on learning and memory before comparing them to the industry standard drug. A total of 42 adult healthy Wistar rats were used in our study. In this experiment, rats were given daily doses of 2.5 mg/kg of body weight of scopolamine hydrobromide for 7 days to induce Alzheimer's disease. On the eighth day, behavioural testing was conducted. Following testing, scopolamine and the test medications were given daily for the following 21 days. On days 29 and 30, behavioural testing was conducted once more, and then animals were slaughtered. Brain homogenate was produced for the estimation of molecular and biochemical markers. Curcumin has demonstrated a dose-response relationship, with a higher dose (200 mg/kg b.w. p.o.) being more effective than a lower dose (100 mg/kg b.w. p.o.). Similar to the greater dose of curcumin, coenzyme Q10 (200 mg/kg b.w. p.o.) has also been found to improve memory and learning. Higher doses of curcumin and coenzyme Q10 had more pronounced and meaningful effects. Acetylcholinesterase and TNF levels increased in scopolamine-induced memory impairment, but these effects were restored by the test medications, and improved by the combined therapy. These outcomes are comparable to those of the common medication memantine. As a result, we may infer from our results that curcumin at higher doses and its combination with coenzyme Q10 (200 mg/kg b.w. p.o.) have a significant impact on cognitive impairment in animal models of Alzheimer's disease and can be utilised alone or as an add-on therapy for the condition.

PurposeIn developed and developing countries, organizations need to do sustainability reporting. The purpose of this paper is to identify the vital linkages of sustainability, which helps to capture the existing waste management practice in sustainable organizations.Design/methodology/approachThis paper reports a mixed-method approach for sustainable organization. Initially, the waste management and sustainability factors have been linked together for finding the relation between them through the situation, actor, process, learning, action, performance (SAP-LAP) linkages framework; it has been used as qualitative design details to achieve sustainability in the organization. The waste management and sustainability factors linkages have been used as a reference to guide the cause and effect relationship through decision-making trial and evaluation laboratory (DEMATEL) to upgrade knowledge for a sustainable organization.FindingsThe proposed method has been used to meet the functional requirements of sustainability in the organization. Waste management has been analyzed as the most significant benchmarks to achieve sustainability in the organization. The causal relationship reveals that the social image of an organization as a sustainable organization is the effect of its governmental directives, followed by the organization. The governmental directives is the most influencing dimension, and waste management efficiency and energy consumption are the most related, whereas wastivity is the most flexible dimension of sustainability in the organization. To increase its customer satisfaction, profit share and market value, these factors must be considered as vital factors of organization's sustainable performance.Research limitations/implicationsThe scope of the present research has been limited to benchmark sustainability by analyzing eight waste management factors and ten critical sustainability factors that have been grouped into four dimensions in the service sector, which could be generalized. The expert's view has been captured for DEMATEL based on “ratings provided by experts,” which may be biased.Practical implicationsBenchmarked sustainability factors have been proposed to increase the value and performance of the organization. The cause and effect relationship is useful to present the capability of waste management to act as a strong foundation for establishing a sustainable organization, where governmental directives, wastivity, waste management efficiency, and energy consumption act as the benchmarking factors to compare sustainable organization performance in developing the county's viewpoint. The present study considered the fourth dimension of sustainability “government and customer” as the dynamic dimension of sustainability, which can absorb and diffuse the changes in sustainable organization with time and can improvise social acceptance.Originality/valueThe research improves the existing method of measuring the performance of the sustainable organization by using well-established methods.

Synonymous codon usage bias is an inevitable phenomenon in organismic taxa across the three domains of life. Though the frequency of codon usage is not equal across species and within genome in the same species, the phenomenon is non random and is tissue-specific. Several factors such as GC content, nucleotide distribution, protein hydropathy, protein secondary structure, and translational selection are reported to contribute to codon usage preference. The synonymous codon usage patterns can be helpful in revealing the expression pattern of genes as well as the evolutionary relationship between the sequences. In this study, synonymous codon usage bias patterns were determined for the evolutionarily close proteins of albumin superfamily, namely, albumin, α-fetoprotein, afamin, and vitamin D-binding protein. Our study demonstrated that the genes of the four albumin superfamily members have low GC content and high values of effective number of codons (ENC) suggesting high expressivity of these genes and less bias in codon usage preferences. This study also provided evidence that the albumin superfamily members are not subjected to mutational selection pressure.

SunPower Corporation is an American organization working in the solar energy sector specialized in power generation and solar energy storage. This case highlights the strategic growth path of SunPower corporation, which originated as an outcome of effective solar cells production. This case also discussed how the energy sector considers solar energy the vital energy source, and solar energy organizations grow to capture the energy demand. The case also highlights the various consolidations of SunPower in terms of different mergers and acquisitions as essential strategies to succeed. The case also discusses the competitors’ strategy of the top five solar power generation and storage firms, which give a clear view of how different solar firms are building their space in the solar energy sector. With competitors’ discussion, this helps to understand the challenge faced by SunPower to beat the competition among the other solar firms. In the end, the case focused on the ongoing and future strategic choices of SunPower as SunPower Corporation.

Dengue is a mosquito-borne viral disease caused by four closely related serotypes of Dengue viruses (DENVs). This disease whose symptoms range from mild fever to potentially fatal haemorrhagic fever and hypovolemic shock, threatens nearly half the global population. There is neither a preventive vaccine nor an effective antiviral therapy against dengue disease. The difference between severe and mild disease appears to be dependent on the viral load. Early diagnosis may enable timely therapeutic intervention to blunt disease severity by reducing the viral load. Harnessing the therapeutic potential of RNA interference (RNAi) to attenuate DENV replication may offer one approach to dengue therapy. We screened the non-translated regions (NTRs) of the RNA genomes of representative members of the four DENV serotypes for putative siRNA targets mapping to known transcription/translation regulatory elements. We identified a target site in the 5' NTR that maps to the 5' upstream AUG region, a highly conserved cis-acting element essential for viral replication. We used a replication-defective human adenovirus type 5 (AdV5) vector to deliver a short-hairpin RNA (shRNA) targeting this site into cells. We show that this shRNA matures to the cognate siRNA and is able to inhibit effectively antigen secretion, viral RNA replication and infectious virus production by all four DENV serotypes. The data demonstrate the feasibility of using AdV5-mediated delivery of shRNAs targeting conserved sites in the viral genome to achieve inhibition of all four DENV serotypes. This paves the way towards exploration of RNAi as a possible therapeutic strategy to curtail DENV infection.

Persistent homology is a method for probing topological properties of point clouds and functions. The method involves tracking the birth and death of topological features (2000) as one varies a tuning parameter. Features with short lifetimes are informally considered to be \"topological noise,\" and those with a long lifetime are considered to be \"topological signal.\" In this paper, we bring some statistical ideas to persistent homology. In particular, we derive confidence sets that allow us to separate topological signal from topological noise.